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rossburton/yocto-autobuilder
refs/heads/ross
lib/python2.7/site-packages/SQLAlchemy-0.7.0-py2.7-linux-x86_64.egg/sqlalchemy/ext/compiler.py
8
# ext/compiler.py # Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file> # # This module is part of SQLAlchemy and is released under # the MIT License: http://www.opensource.org/licenses/mit-license.php """Provides an API for creation of custom ClauseElements and compilers. Synopsis ======== Usage involves the creation of one or more :class:`~sqlalchemy.sql.expression.ClauseElement` subclasses and one or more callables defining its compilation:: from sqlalchemy.ext.compiler import compiles from sqlalchemy.sql.expression import ColumnClause class MyColumn(ColumnClause): pass @compiles(MyColumn) def compile_mycolumn(element, compiler, **kw): return "[%s]" % element.name Above, ``MyColumn`` extends :class:`~sqlalchemy.sql.expression.ColumnClause`, the base expression element for named column objects. The ``compiles`` decorator registers itself with the ``MyColumn`` class so that it is invoked when the object is compiled to a string:: from sqlalchemy import select s = select([MyColumn('x'), MyColumn('y')]) print str(s) Produces:: SELECT [x], [y] Dialect-specific compilation rules ================================== Compilers can also be made dialect-specific. The appropriate compiler will be invoked for the dialect in use:: from sqlalchemy.schema import DDLElement class AlterColumn(DDLElement): def __init__(self, column, cmd): self.column = column self.cmd = cmd @compiles(AlterColumn) def visit_alter_column(element, compiler, **kw): return "ALTER COLUMN %s ..." % element.column.name @compiles(AlterColumn, 'postgresql') def visit_alter_column(element, compiler, **kw): return "ALTER TABLE %s ALTER COLUMN %s ..." % (element.table.name, element.column.name) The second ``visit_alter_table`` will be invoked when any ``postgresql`` dialect is used. Compiling sub-elements of a custom expression construct ======================================================= The ``compiler`` argument is the :class:`~sqlalchemy.engine.base.Compiled` object in use. This object can be inspected for any information about the in-progress compilation, including ``compiler.dialect``, ``compiler.statement`` etc. The :class:`~sqlalchemy.sql.compiler.SQLCompiler` and :class:`~sqlalchemy.sql.compiler.DDLCompiler` both include a ``process()`` method which can be used for compilation of embedded attributes:: from sqlalchemy.sql.expression import Executable, ClauseElement class InsertFromSelect(Executable, ClauseElement): def __init__(self, table, select): self.table = table self.select = select @compiles(InsertFromSelect) def visit_insert_from_select(element, compiler, **kw): return "INSERT INTO %s (%s)" % ( compiler.process(element.table, asfrom=True), compiler.process(element.select) ) insert = InsertFromSelect(t1, select([t1]).where(t1.c.x>5)) print insert Produces:: "INSERT INTO mytable (SELECT mytable.x, mytable.y, mytable.z FROM mytable WHERE mytable.x > :x_1)" Cross Compiling between SQL and DDL compilers --------------------------------------------- SQL and DDL constructs are each compiled using different base compilers - ``SQLCompiler`` and ``DDLCompiler``. A common need is to access the compilation rules of SQL expressions from within a DDL expression. The ``DDLCompiler`` includes an accessor ``sql_compiler`` for this reason, such as below where we generate a CHECK constraint that embeds a SQL expression:: @compiles(MyConstraint) def compile_my_constraint(constraint, ddlcompiler, **kw): return "CONSTRAINT %s CHECK (%s)" % ( constraint.name, ddlcompiler.sql_compiler.process(constraint.expression) ) Changing the default compilation of existing constructs ======================================================= The compiler extension applies just as well to the existing constructs. When overriding the compilation of a built in SQL construct, the @compiles decorator is invoked upon the appropriate class (be sure to use the class, i.e. ``Insert`` or ``Select``, instead of the creation function such as ``insert()`` or ``select()``). Within the new compilation function, to get at the "original" compilation routine, use the appropriate visit_XXX method - this because compiler.process() will call upon the overriding routine and cause an endless loop. Such as, to add "prefix" to all insert statements:: from sqlalchemy.sql.expression import Insert @compiles(Insert) def prefix_inserts(insert, compiler, **kw): return compiler.visit_insert(insert.prefix_with("some prefix"), **kw) The above compiler will prefix all INSERT statements with "some prefix" when compiled. .. _type_compilation_extension: Changing Compilation of Types ============================= ``compiler`` works for types, too, such as below where we implement the MS-SQL specific 'max' keyword for ``String``/``VARCHAR``:: @compiles(String, 'mssql') @compiles(VARCHAR, 'mssql') def compile_varchar(element, compiler, **kw): if element.length == 'max': return "VARCHAR('max')" else: return compiler.visit_VARCHAR(element, **kw) foo = Table('foo', metadata, Column('data', VARCHAR('max')) ) Subclassing Guidelines ====================== A big part of using the compiler extension is subclassing SQLAlchemy expression constructs. To make this easier, the expression and schema packages feature a set of "bases" intended for common tasks. A synopsis is as follows: * :class:`~sqlalchemy.sql.expression.ClauseElement` - This is the root expression class. Any SQL expression can be derived from this base, and is probably the best choice for longer constructs such as specialized INSERT statements. * :class:`~sqlalchemy.sql.expression.ColumnElement` - The root of all "column-like" elements. Anything that you'd place in the "columns" clause of a SELECT statement (as well as order by and group by) can derive from this - the object will automatically have Python "comparison" behavior. :class:`~sqlalchemy.sql.expression.ColumnElement` classes want to have a ``type`` member which is expression's return type. This can be established at the instance level in the constructor, or at the class level if its generally constant:: class timestamp(ColumnElement): type = TIMESTAMP() * :class:`~sqlalchemy.sql.expression.FunctionElement` - This is a hybrid of a ``ColumnElement`` and a "from clause" like object, and represents a SQL function or stored procedure type of call. Since most databases support statements along the line of "SELECT FROM <some function>" ``FunctionElement`` adds in the ability to be used in the FROM clause of a ``select()`` construct:: from sqlalchemy.sql.expression import FunctionElement class coalesce(FunctionElement): name = 'coalesce' @compiles(coalesce) def compile(element, compiler, **kw): return "coalesce(%s)" % compiler.process(element.clauses) @compiles(coalesce, 'oracle') def compile(element, compiler, **kw): if len(element.clauses) > 2: raise TypeError("coalesce only supports two arguments on Oracle") return "nvl(%s)" % compiler.process(element.clauses) * :class:`~sqlalchemy.schema.DDLElement` - The root of all DDL expressions, like CREATE TABLE, ALTER TABLE, etc. Compilation of ``DDLElement`` subclasses is issued by a ``DDLCompiler`` instead of a ``SQLCompiler``. ``DDLElement`` also features ``Table`` and ``MetaData`` event hooks via the ``execute_at()`` method, allowing the construct to be invoked during CREATE TABLE and DROP TABLE sequences. * :class:`~sqlalchemy.sql.expression.Executable` - This is a mixin which should be used with any expression class that represents a "standalone" SQL statement that can be passed directly to an ``execute()`` method. It is already implicit within ``DDLElement`` and ``FunctionElement``. Further Examples ================ "UTC timestamp" function ------------------------- A function that works like "CURRENT_TIMESTAMP" except applies the appropriate conversions so that the time is in UTC time. Timestamps are best stored in relational databases as UTC, without time zones. UTC so that your database doesn't think time has gone backwards in the hour when daylight savings ends, without timezones because timezones are like character encodings - they're best applied only at the endpoints of an application (i.e. convert to UTC upon user input, re-apply desired timezone upon display). For Postgresql and Microsoft SQL Server:: from sqlalchemy.sql import expression from sqlalchemy.ext.compiler import compiles from sqlalchemy.types import DateTime class utcnow(expression.FunctionElement): type = DateTime() @compiles(utcnow, 'postgresql') def pg_utcnow(element, compiler, **kw): return "TIMEZONE('utc', CURRENT_TIMESTAMP)" @compiles(utcnow, 'mssql') def ms_utcnow(element, compiler, **kw): return "GETUTCDATE()" Example usage:: from sqlalchemy import ( Table, Column, Integer, String, DateTime, MetaData ) metadata = MetaData() event = Table("event", metadata, Column("id", Integer, primary_key=True), Column("description", String(50), nullable=False), Column("timestamp", DateTime, server_default=utcnow()) ) "GREATEST" function ------------------- The "GREATEST" function is given any number of arguments and returns the one that is of the highest value - it's equivalent to Python's ``max`` function. A SQL standard version versus a CASE based version which only accommodates two arguments:: from sqlalchemy.sql import expression from sqlalchemy.ext.compiler import compiles from sqlalchemy.types import Numeric class greatest(expression.FunctionElement): type = Numeric() name = 'greatest' @compiles(greatest) def default_greatest(element, compiler, **kw): return compiler.visit_function(element) @compiles(greatest, 'sqlite') @compiles(greatest, 'mssql') @compiles(greatest, 'oracle') def case_greatest(element, compiler, **kw): arg1, arg2 = list(element.clauses) return "CASE WHEN %s > %s THEN %s ELSE %s END" % ( compiler.process(arg1), compiler.process(arg2), compiler.process(arg1), compiler.process(arg2), ) Example usage:: Session.query(Account).\\ filter( greatest( Account.checking_balance, Account.savings_balance) > 10000 ) "false" expression ------------------ Render a "false" constant expression, rendering as "0" on platforms that don't have a "false" constant:: from sqlalchemy.sql import expression from sqlalchemy.ext.compiler import compiles class sql_false(expression.ColumnElement): pass @compiles(sql_false) def default_false(element, compiler, **kw): return "false" @compiles(sql_false, 'mssql') @compiles(sql_false, 'mysql') @compiles(sql_false, 'oracle') def int_false(element, compiler, **kw): return "0" Example usage:: from sqlalchemy import select, union_all exp = union_all( select([users.c.name, sql_false().label("enrolled")]), select([customers.c.name, customers.c.enrolled]) ) """ def compiles(class_, *specs): def decorate(fn): existing = class_.__dict__.get('_compiler_dispatcher', None) existing_dispatch = class_.__dict__.get('_compiler_dispatch') if not existing: existing = _dispatcher() if existing_dispatch: existing.specs['default'] = existing_dispatch # TODO: why is the lambda needed ? setattr(class_, '_compiler_dispatch', lambda *arg, **kw: existing(*arg, **kw)) setattr(class_, '_compiler_dispatcher', existing) if specs: for s in specs: existing.specs[s] = fn else: existing.specs['default'] = fn return fn return decorate class _dispatcher(object): def __init__(self): self.specs = {} def __call__(self, element, compiler, **kw): # TODO: yes, this could also switch off of DBAPI in use. fn = self.specs.get(compiler.dialect.name, None) if not fn: fn = self.specs['default'] return fn(element, compiler, **kw)
acsone/stock-logistics-warehouse
refs/heads/8.0
stock_optional_valuation/__init__.py
23
# -*- coding: utf-8 -*- ############################################################################## # # Copyright (C) 2013 Agile Business Group sagl (<http://www.agilebg.com>) # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ############################################################################## from . import stock
jonathanslenders/python-prompt-toolkit
refs/heads/master
prompt_toolkit/document.py
1
""" The `Document` that implements all the text operations/querying. """ import bisect import re import string import weakref from typing import Callable, Dict, Iterable, List, Optional, Pattern, Tuple, cast from .clipboard import ClipboardData from .filters import vi_mode from .selection import PasteMode, SelectionState, SelectionType __all__ = [ "Document", ] # Regex for finding "words" in documents. (We consider a group of alnum # characters a word, but also a group of special characters a word, as long as # it doesn't contain a space.) # (This is a 'word' in Vi.) _FIND_WORD_RE = re.compile(r"([a-zA-Z0-9_]+|[^a-zA-Z0-9_\s]+)") _FIND_CURRENT_WORD_RE = re.compile(r"^([a-zA-Z0-9_]+|[^a-zA-Z0-9_\s]+)") _FIND_CURRENT_WORD_INCLUDE_TRAILING_WHITESPACE_RE = re.compile( r"^(([a-zA-Z0-9_]+|[^a-zA-Z0-9_\s]+)\s*)" ) # Regex for finding "WORDS" in documents. # (This is a 'WORD in Vi.) _FIND_BIG_WORD_RE = re.compile(r"([^\s]+)") _FIND_CURRENT_BIG_WORD_RE = re.compile(r"^([^\s]+)") _FIND_CURRENT_BIG_WORD_INCLUDE_TRAILING_WHITESPACE_RE = re.compile(r"^([^\s]+\s*)") # Share the Document._cache between all Document instances. # (Document instances are considered immutable. That means that if another # `Document` is constructed with the same text, it should have the same # `_DocumentCache`.) _text_to_document_cache: Dict[str, "_DocumentCache"] = cast( Dict[str, "_DocumentCache"], weakref.WeakValueDictionary(), # Maps document.text to DocumentCache instance. ) class _ImmutableLineList(list): """ Some protection for our 'lines' list, which is assumed to be immutable in the cache. (Useful for detecting obvious bugs.) """ def _error(self, *a: object, **kw: object) -> None: raise NotImplementedError("Attempt to modify an immutable list.") __setitem__ = _error # type: ignore append = _error clear = _error extend = _error insert = _error pop = _error remove = _error reverse = _error sort = _error # type: ignore class _DocumentCache: def __init__(self) -> None: #: List of lines for the Document text. self.lines: Optional[_ImmutableLineList] = None #: List of index positions, pointing to the start of all the lines. self.line_indexes: Optional[List[int]] = None class Document: """ This is a immutable class around the text and cursor position, and contains methods for querying this data, e.g. to give the text before the cursor. This class is usually instantiated by a :class:`~prompt_toolkit.buffer.Buffer` object, and accessed as the `document` property of that class. :param text: string :param cursor_position: int :param selection: :class:`.SelectionState` """ __slots__ = ("_text", "_cursor_position", "_selection", "_cache") def __init__( self, text: str = "", cursor_position: Optional[int] = None, selection: Optional[SelectionState] = None, ) -> None: # Check cursor position. It can also be right after the end. (Where we # insert text.) assert cursor_position is None or cursor_position <= len(text), AssertionError( "cursor_position=%r, len_text=%r" % (cursor_position, len(text)) ) # By default, if no cursor position was given, make sure to put the # cursor position is at the end of the document. This is what makes # sense in most places. if cursor_position is None: cursor_position = len(text) # Keep these attributes private. A `Document` really has to be # considered to be immutable, because otherwise the caching will break # things. Because of that, we wrap these into read-only properties. self._text = text self._cursor_position = cursor_position self._selection = selection # Cache for lines/indexes. (Shared with other Document instances that # contain the same text. try: self._cache = _text_to_document_cache[self.text] except KeyError: self._cache = _DocumentCache() _text_to_document_cache[self.text] = self._cache # XX: For some reason, above, we can't use 'WeakValueDictionary.setdefault'. # This fails in Pypy3. `self._cache` becomes None, because that's what # 'setdefault' returns. # self._cache = _text_to_document_cache.setdefault(self.text, _DocumentCache()) # assert self._cache def __repr__(self) -> str: return "%s(%r, %r)" % (self.__class__.__name__, self.text, self.cursor_position) def __eq__(self, other: object) -> bool: if not isinstance(other, Document): return False return ( self.text == other.text and self.cursor_position == other.cursor_position and self.selection == other.selection ) @property def text(self) -> str: " The document text. " return self._text @property def cursor_position(self) -> int: " The document cursor position. " return self._cursor_position @property def selection(self) -> Optional[SelectionState]: " :class:`.SelectionState` object. " return self._selection @property def current_char(self) -> str: """ Return character under cursor or an empty string. """ return self._get_char_relative_to_cursor(0) or "" @property def char_before_cursor(self) -> str: """ Return character before the cursor or an empty string. """ return self._get_char_relative_to_cursor(-1) or "" @property def text_before_cursor(self) -> str: return self.text[: self.cursor_position :] @property def text_after_cursor(self) -> str: return self.text[self.cursor_position :] @property def current_line_before_cursor(self) -> str: """ Text from the start of the line until the cursor. """ _, _, text = self.text_before_cursor.rpartition("\n") return text @property def current_line_after_cursor(self) -> str: """ Text from the cursor until the end of the line. """ text, _, _ = self.text_after_cursor.partition("\n") return text @property def lines(self) -> List[str]: """ Array of all the lines. """ # Cache, because this one is reused very often. if self._cache.lines is None: self._cache.lines = _ImmutableLineList(self.text.split("\n")) return self._cache.lines @property def _line_start_indexes(self) -> List[int]: """ Array pointing to the start indexes of all the lines. """ # Cache, because this is often reused. (If it is used, it's often used # many times. And this has to be fast for editing big documents!) if self._cache.line_indexes is None: # Create list of line lengths. line_lengths = map(len, self.lines) # Calculate cumulative sums. indexes = [0] append = indexes.append pos = 0 for line_length in line_lengths: pos += line_length + 1 append(pos) # Remove the last item. (This is not a new line.) if len(indexes) > 1: indexes.pop() self._cache.line_indexes = indexes return self._cache.line_indexes @property def lines_from_current(self) -> List[str]: """ Array of the lines starting from the current line, until the last line. """ return self.lines[self.cursor_position_row :] @property def line_count(self) -> int: r"""Return the number of lines in this document. If the document ends with a trailing \n, that counts as the beginning of a new line.""" return len(self.lines) @property def current_line(self) -> str: """Return the text on the line where the cursor is. (when the input consists of just one line, it equals `text`.""" return self.current_line_before_cursor + self.current_line_after_cursor @property def leading_whitespace_in_current_line(self) -> str: """ The leading whitespace in the left margin of the current line. """ current_line = self.current_line length = len(current_line) - len(current_line.lstrip()) return current_line[:length] def _get_char_relative_to_cursor(self, offset: int = 0) -> str: """ Return character relative to cursor position, or empty string """ try: return self.text[self.cursor_position + offset] except IndexError: return "" @property def on_first_line(self) -> bool: """ True when we are at the first line. """ return self.cursor_position_row == 0 @property def on_last_line(self) -> bool: """ True when we are at the last line. """ return self.cursor_position_row == self.line_count - 1 @property def cursor_position_row(self) -> int: """ Current row. (0-based.) """ row, _ = self._find_line_start_index(self.cursor_position) return row @property def cursor_position_col(self) -> int: """ Current column. (0-based.) """ # (Don't use self.text_before_cursor to calculate this. Creating # substrings and doing rsplit is too expensive for getting the cursor # position.) _, line_start_index = self._find_line_start_index(self.cursor_position) return self.cursor_position - line_start_index def _find_line_start_index(self, index: int) -> Tuple[int, int]: """ For the index of a character at a certain line, calculate the index of the first character on that line. Return (row, index) tuple. """ indexes = self._line_start_indexes pos = bisect.bisect_right(indexes, index) - 1 return pos, indexes[pos] def translate_index_to_position(self, index: int) -> Tuple[int, int]: """ Given an index for the text, return the corresponding (row, col) tuple. (0-based. Returns (0, 0) for index=0.) """ # Find start of this line. row, row_index = self._find_line_start_index(index) col = index - row_index return row, col def translate_row_col_to_index(self, row: int, col: int) -> int: """ Given a (row, col) tuple, return the corresponding index. (Row and col params are 0-based.) Negative row/col values are turned into zero. """ try: result = self._line_start_indexes[row] line = self.lines[row] except IndexError: if row < 0: result = self._line_start_indexes[0] line = self.lines[0] else: result = self._line_start_indexes[-1] line = self.lines[-1] result += max(0, min(col, len(line))) # Keep in range. (len(self.text) is included, because the cursor can be # right after the end of the text as well.) result = max(0, min(result, len(self.text))) return result @property def is_cursor_at_the_end(self) -> bool: """ True when the cursor is at the end of the text. """ return self.cursor_position == len(self.text) @property def is_cursor_at_the_end_of_line(self) -> bool: """ True when the cursor is at the end of this line. """ return self.current_char in ("\n", "") def has_match_at_current_position(self, sub: str) -> bool: """ `True` when this substring is found at the cursor position. """ return self.text.find(sub, self.cursor_position) == self.cursor_position def find( self, sub: str, in_current_line: bool = False, include_current_position: bool = False, ignore_case: bool = False, count: int = 1, ) -> Optional[int]: """ Find `text` after the cursor, return position relative to the cursor position. Return `None` if nothing was found. :param count: Find the n-th occurrence. """ assert isinstance(ignore_case, bool) if in_current_line: text = self.current_line_after_cursor else: text = self.text_after_cursor if not include_current_position: if len(text) == 0: return None # (Otherwise, we always get a match for the empty string.) else: text = text[1:] flags = re.IGNORECASE if ignore_case else 0 iterator = re.finditer(re.escape(sub), text, flags) try: for i, match in enumerate(iterator): if i + 1 == count: if include_current_position: return match.start(0) else: return match.start(0) + 1 except StopIteration: pass return None def find_all(self, sub: str, ignore_case: bool = False) -> List[int]: """ Find all occurrences of the substring. Return a list of absolute positions in the document. """ flags = re.IGNORECASE if ignore_case else 0 return [a.start() for a in re.finditer(re.escape(sub), self.text, flags)] def find_backwards( self, sub: str, in_current_line: bool = False, ignore_case: bool = False, count: int = 1, ) -> Optional[int]: """ Find `text` before the cursor, return position relative to the cursor position. Return `None` if nothing was found. :param count: Find the n-th occurrence. """ if in_current_line: before_cursor = self.current_line_before_cursor[::-1] else: before_cursor = self.text_before_cursor[::-1] flags = re.IGNORECASE if ignore_case else 0 iterator = re.finditer(re.escape(sub[::-1]), before_cursor, flags) try: for i, match in enumerate(iterator): if i + 1 == count: return -match.start(0) - len(sub) except StopIteration: pass return None def get_word_before_cursor( self, WORD: bool = False, pattern: Optional[Pattern[str]] = None ) -> str: """ Give the word before the cursor. If we have whitespace before the cursor this returns an empty string. :param pattern: (None or compiled regex). When given, use this regex pattern. """ if self._is_word_before_cursor_complete(WORD=WORD, pattern=pattern): # Space before the cursor or no text before cursor. return "" text_before_cursor = self.text_before_cursor start = self.find_start_of_previous_word(WORD=WORD, pattern=pattern) or 0 return text_before_cursor[len(text_before_cursor) + start :] def _is_word_before_cursor_complete( self, WORD: bool = False, pattern: Optional[Pattern[str]] = None ) -> bool: if pattern: return self.find_start_of_previous_word(WORD=WORD, pattern=pattern) is None else: return ( self.text_before_cursor == "" or self.text_before_cursor[-1:].isspace() ) def find_start_of_previous_word( self, count: int = 1, WORD: bool = False, pattern: Optional[Pattern[str]] = None ) -> Optional[int]: """ Return an index relative to the cursor position pointing to the start of the previous word. Return `None` if nothing was found. :param pattern: (None or compiled regex). When given, use this regex pattern. """ assert not (WORD and pattern) # Reverse the text before the cursor, in order to do an efficient # backwards search. text_before_cursor = self.text_before_cursor[::-1] if pattern: regex = pattern elif WORD: regex = _FIND_BIG_WORD_RE else: regex = _FIND_WORD_RE iterator = regex.finditer(text_before_cursor) try: for i, match in enumerate(iterator): if i + 1 == count: return -match.end(0) except StopIteration: pass return None def find_boundaries_of_current_word( self, WORD: bool = False, include_leading_whitespace: bool = False, include_trailing_whitespace: bool = False, ) -> Tuple[int, int]: """ Return the relative boundaries (startpos, endpos) of the current word under the cursor. (This is at the current line, because line boundaries obviously don't belong to any word.) If not on a word, this returns (0,0) """ text_before_cursor = self.current_line_before_cursor[::-1] text_after_cursor = self.current_line_after_cursor def get_regex(include_whitespace: bool) -> Pattern[str]: return { (False, False): _FIND_CURRENT_WORD_RE, (False, True): _FIND_CURRENT_WORD_INCLUDE_TRAILING_WHITESPACE_RE, (True, False): _FIND_CURRENT_BIG_WORD_RE, (True, True): _FIND_CURRENT_BIG_WORD_INCLUDE_TRAILING_WHITESPACE_RE, }[(WORD, include_whitespace)] match_before = get_regex(include_leading_whitespace).search(text_before_cursor) match_after = get_regex(include_trailing_whitespace).search(text_after_cursor) # When there is a match before and after, and we're not looking for # WORDs, make sure that both the part before and after the cursor are # either in the [a-zA-Z_] alphabet or not. Otherwise, drop the part # before the cursor. if not WORD and match_before and match_after: c1 = self.text[self.cursor_position - 1] c2 = self.text[self.cursor_position] alphabet = string.ascii_letters + "0123456789_" if (c1 in alphabet) != (c2 in alphabet): match_before = None return ( -match_before.end(1) if match_before else 0, match_after.end(1) if match_after else 0, ) def get_word_under_cursor(self, WORD: bool = False) -> str: """ Return the word, currently below the cursor. This returns an empty string when the cursor is on a whitespace region. """ start, end = self.find_boundaries_of_current_word(WORD=WORD) return self.text[self.cursor_position + start : self.cursor_position + end] def find_next_word_beginning( self, count: int = 1, WORD: bool = False ) -> Optional[int]: """ Return an index relative to the cursor position pointing to the start of the next word. Return `None` if nothing was found. """ if count < 0: return self.find_previous_word_beginning(count=-count, WORD=WORD) regex = _FIND_BIG_WORD_RE if WORD else _FIND_WORD_RE iterator = regex.finditer(self.text_after_cursor) try: for i, match in enumerate(iterator): # Take first match, unless it's the word on which we're right now. if i == 0 and match.start(1) == 0: count += 1 if i + 1 == count: return match.start(1) except StopIteration: pass return None def find_next_word_ending( self, include_current_position: bool = False, count: int = 1, WORD: bool = False ) -> Optional[int]: """ Return an index relative to the cursor position pointing to the end of the next word. Return `None` if nothing was found. """ if count < 0: return self.find_previous_word_ending(count=-count, WORD=WORD) if include_current_position: text = self.text_after_cursor else: text = self.text_after_cursor[1:] regex = _FIND_BIG_WORD_RE if WORD else _FIND_WORD_RE iterable = regex.finditer(text) try: for i, match in enumerate(iterable): if i + 1 == count: value = match.end(1) if include_current_position: return value else: return value + 1 except StopIteration: pass return None def find_previous_word_beginning( self, count: int = 1, WORD: bool = False ) -> Optional[int]: """ Return an index relative to the cursor position pointing to the start of the previous word. Return `None` if nothing was found. """ if count < 0: return self.find_next_word_beginning(count=-count, WORD=WORD) regex = _FIND_BIG_WORD_RE if WORD else _FIND_WORD_RE iterator = regex.finditer(self.text_before_cursor[::-1]) try: for i, match in enumerate(iterator): if i + 1 == count: return -match.end(1) except StopIteration: pass return None def find_previous_word_ending( self, count: int = 1, WORD: bool = False ) -> Optional[int]: """ Return an index relative to the cursor position pointing to the end of the previous word. Return `None` if nothing was found. """ if count < 0: return self.find_next_word_ending(count=-count, WORD=WORD) text_before_cursor = self.text_after_cursor[:1] + self.text_before_cursor[::-1] regex = _FIND_BIG_WORD_RE if WORD else _FIND_WORD_RE iterator = regex.finditer(text_before_cursor) try: for i, match in enumerate(iterator): # Take first match, unless it's the word on which we're right now. if i == 0 and match.start(1) == 0: count += 1 if i + 1 == count: return -match.start(1) + 1 except StopIteration: pass return None def find_next_matching_line( self, match_func: Callable[[str], bool], count: int = 1 ) -> Optional[int]: """ Look downwards for empty lines. Return the line index, relative to the current line. """ result = None for index, line in enumerate(self.lines[self.cursor_position_row + 1 :]): if match_func(line): result = 1 + index count -= 1 if count == 0: break return result def find_previous_matching_line( self, match_func: Callable[[str], bool], count: int = 1 ) -> Optional[int]: """ Look upwards for empty lines. Return the line index, relative to the current line. """ result = None for index, line in enumerate(self.lines[: self.cursor_position_row][::-1]): if match_func(line): result = -1 - index count -= 1 if count == 0: break return result def get_cursor_left_position(self, count: int = 1) -> int: """ Relative position for cursor left. """ if count < 0: return self.get_cursor_right_position(-count) return -min(self.cursor_position_col, count) def get_cursor_right_position(self, count: int = 1) -> int: """ Relative position for cursor_right. """ if count < 0: return self.get_cursor_left_position(-count) return min(count, len(self.current_line_after_cursor)) def get_cursor_up_position( self, count: int = 1, preferred_column: Optional[int] = None ) -> int: """ Return the relative cursor position (character index) where we would be if the user pressed the arrow-up button. :param preferred_column: When given, go to this column instead of staying at the current column. """ assert count >= 1 column = ( self.cursor_position_col if preferred_column is None else preferred_column ) return ( self.translate_row_col_to_index( max(0, self.cursor_position_row - count), column ) - self.cursor_position ) def get_cursor_down_position( self, count: int = 1, preferred_column: Optional[int] = None ) -> int: """ Return the relative cursor position (character index) where we would be if the user pressed the arrow-down button. :param preferred_column: When given, go to this column instead of staying at the current column. """ assert count >= 1 column = ( self.cursor_position_col if preferred_column is None else preferred_column ) return ( self.translate_row_col_to_index(self.cursor_position_row + count, column) - self.cursor_position ) def find_enclosing_bracket_right( self, left_ch: str, right_ch: str, end_pos: Optional[int] = None ) -> Optional[int]: """ Find the right bracket enclosing current position. Return the relative position to the cursor position. When `end_pos` is given, don't look past the position. """ if self.current_char == right_ch: return 0 if end_pos is None: end_pos = len(self.text) else: end_pos = min(len(self.text), end_pos) stack = 1 # Look forward. for i in range(self.cursor_position + 1, end_pos): c = self.text[i] if c == left_ch: stack += 1 elif c == right_ch: stack -= 1 if stack == 0: return i - self.cursor_position return None def find_enclosing_bracket_left( self, left_ch: str, right_ch: str, start_pos: Optional[int] = None ) -> Optional[int]: """ Find the left bracket enclosing current position. Return the relative position to the cursor position. When `start_pos` is given, don't look past the position. """ if self.current_char == left_ch: return 0 if start_pos is None: start_pos = 0 else: start_pos = max(0, start_pos) stack = 1 # Look backward. for i in range(self.cursor_position - 1, start_pos - 1, -1): c = self.text[i] if c == right_ch: stack += 1 elif c == left_ch: stack -= 1 if stack == 0: return i - self.cursor_position return None def find_matching_bracket_position( self, start_pos: Optional[int] = None, end_pos: Optional[int] = None ) -> int: """ Return relative cursor position of matching [, (, { or < bracket. When `start_pos` or `end_pos` are given. Don't look past the positions. """ # Look for a match. for pair in "()", "[]", "{}", "<>": A = pair[0] B = pair[1] if self.current_char == A: return self.find_enclosing_bracket_right(A, B, end_pos=end_pos) or 0 elif self.current_char == B: return self.find_enclosing_bracket_left(A, B, start_pos=start_pos) or 0 return 0 def get_start_of_document_position(self) -> int: """ Relative position for the start of the document. """ return -self.cursor_position def get_end_of_document_position(self) -> int: """ Relative position for the end of the document. """ return len(self.text) - self.cursor_position def get_start_of_line_position(self, after_whitespace: bool = False) -> int: """ Relative position for the start of this line. """ if after_whitespace: current_line = self.current_line return ( len(current_line) - len(current_line.lstrip()) - self.cursor_position_col ) else: return -len(self.current_line_before_cursor) def get_end_of_line_position(self) -> int: """ Relative position for the end of this line. """ return len(self.current_line_after_cursor) def last_non_blank_of_current_line_position(self) -> int: """ Relative position for the last non blank character of this line. """ return len(self.current_line.rstrip()) - self.cursor_position_col - 1 def get_column_cursor_position(self, column: int) -> int: """ Return the relative cursor position for this column at the current line. (It will stay between the boundaries of the line in case of a larger number.) """ line_length = len(self.current_line) current_column = self.cursor_position_col column = max(0, min(line_length, column)) return column - current_column def selection_range( self, ) -> Tuple[ int, int ]: # XXX: shouldn't this return `None` if there is no selection??? """ Return (from, to) tuple of the selection. start and end position are included. This doesn't take the selection type into account. Use `selection_ranges` instead. """ if self.selection: from_, to = sorted( [self.cursor_position, self.selection.original_cursor_position] ) else: from_, to = self.cursor_position, self.cursor_position return from_, to def selection_ranges(self) -> Iterable[Tuple[int, int]]: """ Return a list of `(from, to)` tuples for the selection or none if nothing was selected. The upper boundary is not included. This will yield several (from, to) tuples in case of a BLOCK selection. This will return zero ranges, like (8,8) for empty lines in a block selection. """ if self.selection: from_, to = sorted( [self.cursor_position, self.selection.original_cursor_position] ) if self.selection.type == SelectionType.BLOCK: from_line, from_column = self.translate_index_to_position(from_) to_line, to_column = self.translate_index_to_position(to) from_column, to_column = sorted([from_column, to_column]) lines = self.lines if vi_mode(): to_column += 1 for l in range(from_line, to_line + 1): line_length = len(lines[l]) if from_column <= line_length: yield ( self.translate_row_col_to_index(l, from_column), self.translate_row_col_to_index( l, min(line_length, to_column) ), ) else: # In case of a LINES selection, go to the start/end of the lines. if self.selection.type == SelectionType.LINES: from_ = max(0, self.text.rfind("\n", 0, from_) + 1) if self.text.find("\n", to) >= 0: to = self.text.find("\n", to) else: to = len(self.text) - 1 # In Vi mode, the upper boundary is always included. For Emacs, # that's not the case. if vi_mode(): to += 1 yield from_, to def selection_range_at_line(self, row: int) -> Optional[Tuple[int, int]]: """ If the selection spans a portion of the given line, return a (from, to) tuple. The returned upper boundary is not included in the selection, so `(0, 0)` is an empty selection. `(0, 1)`, is a one character selection. Returns None if the selection doesn't cover this line at all. """ if self.selection: line = self.lines[row] row_start = self.translate_row_col_to_index(row, 0) row_end = self.translate_row_col_to_index(row, len(line)) from_, to = sorted( [self.cursor_position, self.selection.original_cursor_position] ) # Take the intersection of the current line and the selection. intersection_start = max(row_start, from_) intersection_end = min(row_end, to) if intersection_start <= intersection_end: if self.selection.type == SelectionType.LINES: intersection_start = row_start intersection_end = row_end elif self.selection.type == SelectionType.BLOCK: _, col1 = self.translate_index_to_position(from_) _, col2 = self.translate_index_to_position(to) col1, col2 = sorted([col1, col2]) if col1 > len(line): return None # Block selection doesn't cross this line. intersection_start = self.translate_row_col_to_index(row, col1) intersection_end = self.translate_row_col_to_index(row, col2) _, from_column = self.translate_index_to_position(intersection_start) _, to_column = self.translate_index_to_position(intersection_end) # In Vi mode, the upper boundary is always included. For Emacs # mode, that's not the case. if vi_mode(): to_column += 1 return from_column, to_column return None def cut_selection(self) -> Tuple["Document", ClipboardData]: """ Return a (:class:`.Document`, :class:`.ClipboardData`) tuple, where the document represents the new document when the selection is cut, and the clipboard data, represents whatever has to be put on the clipboard. """ if self.selection: cut_parts = [] remaining_parts = [] new_cursor_position = self.cursor_position last_to = 0 for from_, to in self.selection_ranges(): if last_to == 0: new_cursor_position = from_ remaining_parts.append(self.text[last_to:from_]) cut_parts.append(self.text[from_:to]) last_to = to remaining_parts.append(self.text[last_to:]) cut_text = "\n".join(cut_parts) remaining_text = "".join(remaining_parts) # In case of a LINES selection, don't include the trailing newline. if self.selection.type == SelectionType.LINES and cut_text.endswith("\n"): cut_text = cut_text[:-1] return ( Document(text=remaining_text, cursor_position=new_cursor_position), ClipboardData(cut_text, self.selection.type), ) else: return self, ClipboardData("") def paste_clipboard_data( self, data: ClipboardData, paste_mode: PasteMode = PasteMode.EMACS, count: int = 1, ) -> "Document": """ Return a new :class:`.Document` instance which contains the result if we would paste this data at the current cursor position. :param paste_mode: Where to paste. (Before/after/emacs.) :param count: When >1, Paste multiple times. """ before = paste_mode == PasteMode.VI_BEFORE after = paste_mode == PasteMode.VI_AFTER if data.type == SelectionType.CHARACTERS: if after: new_text = ( self.text[: self.cursor_position + 1] + data.text * count + self.text[self.cursor_position + 1 :] ) else: new_text = ( self.text_before_cursor + data.text * count + self.text_after_cursor ) new_cursor_position = self.cursor_position + len(data.text) * count if before: new_cursor_position -= 1 elif data.type == SelectionType.LINES: l = self.cursor_position_row if before: lines = self.lines[:l] + [data.text] * count + self.lines[l:] new_text = "\n".join(lines) new_cursor_position = len("".join(self.lines[:l])) + l else: lines = self.lines[: l + 1] + [data.text] * count + self.lines[l + 1 :] new_cursor_position = len("".join(self.lines[: l + 1])) + l + 1 new_text = "\n".join(lines) elif data.type == SelectionType.BLOCK: lines = self.lines[:] start_line = self.cursor_position_row start_column = self.cursor_position_col + (0 if before else 1) for i, line in enumerate(data.text.split("\n")): index = i + start_line if index >= len(lines): lines.append("") lines[index] = lines[index].ljust(start_column) lines[index] = ( lines[index][:start_column] + line * count + lines[index][start_column:] ) new_text = "\n".join(lines) new_cursor_position = self.cursor_position + (0 if before else 1) return Document(text=new_text, cursor_position=new_cursor_position) def empty_line_count_at_the_end(self) -> int: """ Return number of empty lines at the end of the document. """ count = 0 for line in self.lines[::-1]: if not line or line.isspace(): count += 1 else: break return count def start_of_paragraph(self, count: int = 1, before: bool = False) -> int: """ Return the start of the current paragraph. (Relative cursor position.) """ def match_func(text: str) -> bool: return not text or text.isspace() line_index = self.find_previous_matching_line( match_func=match_func, count=count ) if line_index: add = 0 if before else 1 return min(0, self.get_cursor_up_position(count=-line_index) + add) else: return -self.cursor_position def end_of_paragraph(self, count: int = 1, after: bool = False) -> int: """ Return the end of the current paragraph. (Relative cursor position.) """ def match_func(text: str) -> bool: return not text or text.isspace() line_index = self.find_next_matching_line(match_func=match_func, count=count) if line_index: add = 0 if after else 1 return max(0, self.get_cursor_down_position(count=line_index) - add) else: return len(self.text_after_cursor) # Modifiers. def insert_after(self, text: str) -> "Document": """ Create a new document, with this text inserted after the buffer. It keeps selection ranges and cursor position in sync. """ return Document( text=self.text + text, cursor_position=self.cursor_position, selection=self.selection, ) def insert_before(self, text: str) -> "Document": """ Create a new document, with this text inserted before the buffer. It keeps selection ranges and cursor position in sync. """ selection_state = self.selection if selection_state: selection_state = SelectionState( original_cursor_position=selection_state.original_cursor_position + len(text), type=selection_state.type, ) return Document( text=text + self.text, cursor_position=self.cursor_position + len(text), selection=selection_state, )
neavouli/yournextrepresentative
refs/heads/release-neavouli
candidates/tests/test_date_parsing.py
1
from __future__ import unicode_literals from django.test import TestCase from django.test.utils import override_settings from django.utils.translation import override from django_date_extensions.fields import ApproximateDate from candidates.models import parse_approximate_date # These tests supplement the doctests; they're not done as # doctests because we need to override settings to pick # either US or non-US day/month default ordering: class DateParsingTests(TestCase): def test_only_year(self): parsed = parse_approximate_date('1977') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1977-00-00') def test_iso_8601(self): parsed = parse_approximate_date('1977-04-01') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1977-04-01') def test_nonsense(self): with self.assertRaises(ValueError): parse_approximate_date('12345678') def test_dd_mm_yyyy_with_slashes(self): parsed = parse_approximate_date('1/4/1977') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1977-04-01') @override_settings(DD_MM_DATE_FORMAT_PREFERRED=False) def test_mm_dd_yyyy_with_slashes(self): parsed = parse_approximate_date('4/1/1977') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1977-04-01') def test_dd_mm_yyyy_with_dashes(self): parsed = parse_approximate_date('1-4-1977') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1977-04-01') def test_natural_date_string(self): parsed = parse_approximate_date('31st December 1999') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1999-12-31') def test_empty_string(self): with self.assertRaises(ValueError): parse_approximate_date('') def test_expanded_natural_date_string(self): parsed = parse_approximate_date('31st of December 1999') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1999-12-31') def test_nonsense_string(self): with self.assertRaises(ValueError): parse_approximate_date('this is not a date') def test_spanish_date_string(self): with self.assertRaises(ValueError): parsed = parse_approximate_date('20 febrero 1954 ') with override('es'): parsed = parse_approximate_date('20 febrero 1954 ') self.assertEqual(type(parsed), ApproximateDate) self.assertEqual(repr(parsed), '1954-02-20')
temasek/android_external_chromium_org
refs/heads/cm-11.0
third_party/protobuf/python/google/protobuf/internal/message_listener.py
590
# Protocol Buffers - Google's data interchange format # Copyright 2008 Google Inc. All rights reserved. # http://code.google.com/p/protobuf/ # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of Google Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """Defines a listener interface for observing certain state transitions on Message objects. Also defines a null implementation of this interface. """ __author__ = 'robinson@google.com (Will Robinson)' class MessageListener(object): """Listens for modifications made to a message. Meant to be registered via Message._SetListener(). Attributes: dirty: If True, then calling Modified() would be a no-op. This can be used to avoid these calls entirely in the common case. """ def Modified(self): """Called every time the message is modified in such a way that the parent message may need to be updated. This currently means either: (a) The message was modified for the first time, so the parent message should henceforth mark the message as present. (b) The message's cached byte size became dirty -- i.e. the message was modified for the first time after a previous call to ByteSize(). Therefore the parent should also mark its byte size as dirty. Note that (a) implies (b), since new objects start out with a client cached size (zero). However, we document (a) explicitly because it is important. Modified() will *only* be called in response to one of these two events -- not every time the sub-message is modified. Note that if the listener's |dirty| attribute is true, then calling Modified at the moment would be a no-op, so it can be skipped. Performance- sensitive callers should check this attribute directly before calling since it will be true most of the time. """ raise NotImplementedError class NullMessageListener(object): """No-op MessageListener implementation.""" def Modified(self): pass
jamespcole/home-assistant
refs/heads/master
homeassistant/components/onvif/__init__.py
15
"""The onvif component."""
davidgbe/scikit-learn
refs/heads/master
examples/decomposition/plot_pca_vs_fa_model_selection.py
142
""" =============================================================== Model selection with Probabilistic PCA and Factor Analysis (FA) =============================================================== Probabilistic PCA and Factor Analysis are probabilistic models. The consequence is that the likelihood of new data can be used for model selection and covariance estimation. Here we compare PCA and FA with cross-validation on low rank data corrupted with homoscedastic noise (noise variance is the same for each feature) or heteroscedastic noise (noise variance is the different for each feature). In a second step we compare the model likelihood to the likelihoods obtained from shrinkage covariance estimators. One can observe that with homoscedastic noise both FA and PCA succeed in recovering the size of the low rank subspace. The likelihood with PCA is higher than FA in this case. However PCA fails and overestimates the rank when heteroscedastic noise is present. Under appropriate circumstances the low rank models are more likely than shrinkage models. The automatic estimation from Automatic Choice of Dimensionality for PCA. NIPS 2000: 598-604 by Thomas P. Minka is also compared. """ print(__doc__) # Authors: Alexandre Gramfort # Denis A. Engemann # License: BSD 3 clause import numpy as np import matplotlib.pyplot as plt from scipy import linalg from sklearn.decomposition import PCA, FactorAnalysis from sklearn.covariance import ShrunkCovariance, LedoitWolf from sklearn.cross_validation import cross_val_score from sklearn.grid_search import GridSearchCV ############################################################################### # Create the data n_samples, n_features, rank = 1000, 50, 10 sigma = 1. rng = np.random.RandomState(42) U, _, _ = linalg.svd(rng.randn(n_features, n_features)) X = np.dot(rng.randn(n_samples, rank), U[:, :rank].T) # Adding homoscedastic noise X_homo = X + sigma * rng.randn(n_samples, n_features) # Adding heteroscedastic noise sigmas = sigma * rng.rand(n_features) + sigma / 2. X_hetero = X + rng.randn(n_samples, n_features) * sigmas ############################################################################### # Fit the models n_components = np.arange(0, n_features, 5) # options for n_components def compute_scores(X): pca = PCA() fa = FactorAnalysis() pca_scores, fa_scores = [], [] for n in n_components: pca.n_components = n fa.n_components = n pca_scores.append(np.mean(cross_val_score(pca, X))) fa_scores.append(np.mean(cross_val_score(fa, X))) return pca_scores, fa_scores def shrunk_cov_score(X): shrinkages = np.logspace(-2, 0, 30) cv = GridSearchCV(ShrunkCovariance(), {'shrinkage': shrinkages}) return np.mean(cross_val_score(cv.fit(X).best_estimator_, X)) def lw_score(X): return np.mean(cross_val_score(LedoitWolf(), X)) for X, title in [(X_homo, 'Homoscedastic Noise'), (X_hetero, 'Heteroscedastic Noise')]: pca_scores, fa_scores = compute_scores(X) n_components_pca = n_components[np.argmax(pca_scores)] n_components_fa = n_components[np.argmax(fa_scores)] pca = PCA(n_components='mle') pca.fit(X) n_components_pca_mle = pca.n_components_ print("best n_components by PCA CV = %d" % n_components_pca) print("best n_components by FactorAnalysis CV = %d" % n_components_fa) print("best n_components by PCA MLE = %d" % n_components_pca_mle) plt.figure() plt.plot(n_components, pca_scores, 'b', label='PCA scores') plt.plot(n_components, fa_scores, 'r', label='FA scores') plt.axvline(rank, color='g', label='TRUTH: %d' % rank, linestyle='-') plt.axvline(n_components_pca, color='b', label='PCA CV: %d' % n_components_pca, linestyle='--') plt.axvline(n_components_fa, color='r', label='FactorAnalysis CV: %d' % n_components_fa, linestyle='--') plt.axvline(n_components_pca_mle, color='k', label='PCA MLE: %d' % n_components_pca_mle, linestyle='--') # compare with other covariance estimators plt.axhline(shrunk_cov_score(X), color='violet', label='Shrunk Covariance MLE', linestyle='-.') plt.axhline(lw_score(X), color='orange', label='LedoitWolf MLE' % n_components_pca_mle, linestyle='-.') plt.xlabel('nb of components') plt.ylabel('CV scores') plt.legend(loc='lower right') plt.title(title) plt.show()
PyWaw/pywaw.org
refs/heads/master
pywaw/meetups/forms.py
1
from django import forms from django.core.exceptions import ValidationError from meetups.constants import EITHER_EXISTING_OR_NEW_SPEAKER_ERROR from . import models class TalkProposalForm(forms.ModelForm): talk_title = forms.CharField() talk_description = forms.CharField(max_length=1000, widget=forms.Textarea) speaker = forms.ModelChoiceField( queryset=models.Speaker.objects.filter(talks__meetup__isnull=False).distinct(), required=False, ) speaker_first_name = forms.CharField(required=False, max_length=30) speaker_last_name = forms.CharField(required=False, max_length=30) speaker_website = forms.URLField(required=False) speaker_phone = forms.CharField(required=False, max_length=30) speaker_email = forms.EmailField(required=False) speaker_biography = forms.CharField(required=False, widget=forms.Textarea) speaker_photo = forms.ImageField(required=False) REQUIRED_SPEAKER_FIELDS = [ 'speaker_first_name', 'speaker_last_name', 'speaker_phone', 'speaker_email', 'speaker_biography', 'speaker_photo', ] class Meta: model = models.TalkProposal fields = ('message',) def save(self, *args, **kwargs): talk_proposal = super().save(commit=False) talk = models.Talk.objects.create( title=self.cleaned_data['talk_title'], description=self.cleaned_data['talk_description'], ) if self.cleaned_data['speaker']: speaker = self.cleaned_data['speaker'] else: speaker = models.Speaker.objects.create( first_name=self.cleaned_data['speaker_first_name'], last_name=self.cleaned_data['speaker_last_name'], website=self.cleaned_data['speaker_website'], phone=self.cleaned_data['speaker_phone'], email=self.cleaned_data['speaker_email'], biography=self.cleaned_data['speaker_biography'], photo=self.cleaned_data['speaker_photo'], ) talk.speakers.add(speaker) talk_proposal.talk = talk talk_proposal.save() return talk_proposal def clean(self): if self._existing_speaker_field_empty(): if self._all_required_new_speaker_fields_empty(): raise ValidationError(EITHER_EXISTING_OR_NEW_SPEAKER_ERROR) elif not self._all_required_new_speaker_fields_empty(): for field_name in self.REQUIRED_SPEAKER_FIELDS: if self.cleaned_data.get(field_name) in ['', None]: self._errors[field_name] = self.fields[field_name].error_messages['required'] return self.cleaned_data def _all_required_new_speaker_fields_empty(self): return all(self.cleaned_data.get(field_name) == '' for field_name in self.REQUIRED_SPEAKER_FIELDS) def _existing_speaker_field_empty(self): return not self.cleaned_data['speaker']
ricardogtx/estudoDjango
refs/heads/master
simplemooc/core/tests.py
1
from django.test import TestCase from django.core import mail from django.test.client import Client from django.urls import reverse class HomeViewTest(TestCase): def test_home_status_code(self): client = Client() response = client.get(reverse('core:home')) self.assertEqual(response.status_code, 200) def test_home_template_used(self): client = Client() response = client.get(reverse('core:home')) self.assertTemplateUsed(response, 'home.html') self.assertTemplateUsed(response, 'base.html')
micolous/intuition
refs/heads/master
src/intuition/protocol.py
1
""" intuition/protocol.py - Twisted protocol library for OWL Intuition's multicast UDP energy monitoring protocol. Copyright 2013-2014 Michael Farrell <micolous+git@gmail.com> Copyright 2013 Johan van den Dorpe <johan.vandendorpe@gmail.com> This library is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library. If not, see <http://www.gnu.org/licenses/>. """ from warnings import warn from twisted.internet.protocol import DatagramProtocol from lxml import objectify from decimal import Decimal MCAST_ADDR = '224.192.32.19' MCAST_PORT = 22600 class OwlBaseMessage(object): @property def mac(self): """ MAC Address of the Network Owl. This information comes from the body of the multicast UDP traffic (not the ethernet headers), so may be spoofed. """ return self._mac @property def rssi(self): """ Recieve signal strength (dBm). """ return self._rssi @property def lqi(self): """ Link quality, with 0 being best. """ return self._lqi class OwlChannel(object): # structure for storing data about electricity channels def __init__(self, channel_id, current_w, daily_wh): self._channel_id = channel_id self._current_w = Decimal(current_w) self._daily_wh = Decimal(daily_wh) @property def channel_id(self): return self._channel_id @property def current_w(self): return self._current_w @property def daily_wh(self): return self._daily_wh def __str__(self): return '<OwlChannel: id=%s, current=%s, today=%s>' % ( self.channel_id, self.current_w, self.daily_wh ) class OwlTemperature(object): def __init__(self, zone, current_temp, required_temp): self._zone = zone self._current_temp = Decimal(current_temp) self._required_temp = Decimal(required_temp) @property def zone_id(self): """ Unique identifier for the zone. """ return self._zone @property def current_temp(self): """ The current temperature in the zone. Units are undefined by the documentation, but appear to be degrees Celcius. """ return self._current_temp @property def required_temp(self): """ The desired temperature in the zone. Units are undefined by the documentation, but appear to be degrees Celcius. """ return self._required_temp def __str__(self): return '<OwlTemperature: id=%s, current=%s C, required=%s C>' % ( self.zone_id, self.current_temp, self.required_temp ) class OwlHeating(OwlBaseMessage): def __init__(self, datagram): # TODO: support Network Owl 2.3 assert (datagram.tag == 'heating'), ('OwlHeating XML must have `heating` root node (got %r).' % datagram.tag) self._mac = datagram.attrib['id'] # read signal information for the sensor's 433MHz link self._rssi = Decimal(datagram.signal[0].attrib['rssi']) self._lqi = Decimal(datagram.signal[0].attrib['lqi']) # read battery information from the sensor. self._battery_mv = Decimal(datagram.battery[0].attrib['level'][:-2]) self._zones = {} for temp in datagram.temperature: assert temp.attrib['zone'] not in self._zones self._zones[temp.attrib['zone']] = OwlTemperature(temp.attrib['zone'], temp.current[0].text, temp.required[0].text) @property def battery_mv(self): """ Voltage level of the battery in the sensor, in millivolts. """ return self._battery_mv @property def zones(self): """ Zones defined for managing heating. """ return self._zones def __str__(self): return '<OwlHeating: rssi=%s, lqi=%s, battery=%s mV, zones=%s>' % ( self.rssi, self.lqi, self.battery_mv, ', '.join((str(x) for x in self.zones.itervalues())) ) class OwlElectricity(OwlBaseMessage): def __init__(self, datagram): assert (datagram.tag == 'electricity'), ('OwlElectricity XML must have `electricity` root node (got %r).' % datagram.tag) self._mac = datagram.attrib['id'] # read signal information for the sensor's 433MHz link self._rssi = Decimal(datagram.signal[0].attrib['rssi']) self._lqi = Decimal(datagram.signal[0].attrib['lqi']) # read battery information from the sensor. self._battery_pc = Decimal(datagram.battery[0].attrib['level'][:-1]) # read sensors (channels) self._channels = {} for channel in datagram.chan: assert channel.attrib['id'] not in self._channels, 'Channel duplicate' assert channel.curr[0].attrib['units'] == 'w', 'Current units must be watts' assert channel.day[0].attrib['units'] == 'wh', 'Daily usage must be watthours' # we're good and done our tests, create a channel self._channels[channel.attrib['id']] = OwlChannel(channel.attrib['id'], channel.curr[0].text, channel.day[0].text) @property def battery_pc(self): """ Percentage of battery remaining. Only on OwlElectricity messages. """ return self._battery_pc @property def battery(self): """ Deprecated: use OwlElectricity.battery_pc instead. """ warn('Use OwlElectricity.battery_pc instead.', DeprecationWarning, stacklevel=2) return self.battery_pc @property def channels(self): return self._channels def __str__(self): return '<OwlElectricity: rssi=%s, lqi=%s, battery=%s%%, channels=%s>' % ( self.rssi, self.lqi, self.battery_pc, ', '.join((str(x) for x in self.channels.itervalues())) ) def parse_datagram(datagram): """ Parses a Network Owl datagram. """ xml = objectify.fromstring(datagram) if xml.tag == 'electricity': msg = OwlElectricity(xml) elif xml.tag == 'heating': # note: requires network owl 2.2 # TODO: implement network owl 2.3 support msg = OwlHeating(xml) else: raise NotImplementedError, 'Message type %r not implemented.' % msg.tag return msg class OwlIntuitionProtocol(DatagramProtocol): def __init__(self, iface=''): """ Protocol for Owl Intution (Network Owl) multicast UDP. :param iface: Name of the interface to use to communicate with the Network Owl. If not specified, uses the default network connection on the cost. :type iface: str """ self.iface = iface def startProtocol(self): self.transport.joinGroup(MCAST_ADDR, self.iface) def datagramReceived(self, datagram, address): msg = parse_datagram(datagram) self.owlReceived(address, msg) def owlReceived(self, address, msg): # for the test program print '%s: %s' % (address, msg) if __name__ == '__main__': # pragma: no cover # Simple test program! from twisted.internet import reactor from argparse import ArgumentParser parser = ArgumentParser() parser.add_argument('-i', '--iface', dest='iface', default='', help='Network interface to use for getting data.') options = parser.parse_args() protocol = OwlIntuitionProtocol(iface=options.iface) reactor.listenMulticast(MCAST_PORT, protocol, listenMultiple=True) reactor.run()
camptocamp/c2c-rd-addons
refs/heads/8.0
c2c_account_closing_remarks/__openerp__.py
4
# -*- coding: utf-8 -*- ############################################################################## # # OpenERP, Open Source Management Solution # Copyright (C) 2004-2011 Tiny SPRL (<http://tiny.be>). # Copyright (C) 2010-2011 ChriCar Beteiligungs- und Beratungs- GmbH (<http://www.camptocamp.at>) # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as # published by the Free Software Foundation, either version 3 of the # License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ############################################################################## { 'sequence': 500, 'name': 'Account Closing Remarks', 'version': '0.7', 'category': 'Accounting & Finance', 'description': """ Add a per year textbox for description of account closing remarks """, 'author': 'ChriCar Beteiligungs- und Beratungs- GmbH', 'depends': [ 'account' ], 'data': ['account_view.xml','security/ir.model.access.csv' ], 'demo_xml': [], 'installable': False, 'active': False, } # vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:
shibumi/yowsup
refs/heads/master
src/Yowsup/Contacts/contacts.py
18
''' Copyright (c) <2012> Tarek Galal <tare2.galal@gmail.com> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ''' from Yowsup.Common.Http.warequest import WARequest from Yowsup.Common.Http.waresponseparser import JSONResponseParser from hashlib import md5 import random, sys from Yowsup.Common.utilities import Utilities class WAContactsSyncRequest(): def __init__(self, username, password, contacts): self.username = username self.password = password self.contacts = contacts self.authReq = WAContactsSyncAuth(username, password) def setCredentials(self, username, password): self.username = username self.password = password self.authReq = WAContactsSyncAuth(username, password) def setContacts(self, contacts): self.contacts = contacts def send(self): auth = self.authReq.send() if not auth["message"] == "next token": return auth response = self.authReq.response respH = response.getheader("www-authenticate") self.authReq._d(respH) tmp = respH[respH.index('nonce="')+len('nonce="'):] nonce = tmp[:tmp.index('"')] q = WAContactsSyncQuery(self.username, self.password, nonce, self.contacts) resp = q.send() return resp class WAContactsSyncAuth(WARequest): nc = "00000001" realm = "s.whatsapp.net" qop = "auth" digestUri = "WAWA/s.whatsapp.net" charSet = "utf-8" authMethod = "X-WAWA" authTemplate = '{auth_method}: username="{username}",realm="{realm}",nonce="{nonce}",cnonce="{cnonce}",nc="{nc}",qop="auth",\ digest-uri="{digest_uri}",response="{response}",charset="utf-8"' def __init__(self, username, password, nonce = "0"): super(WAContactsSyncAuth, self).__init__(); self.url = "sro.whatsapp.net/v2/sync/a" self.type = "POST" cnonce = Utilities.str(random.randint(100000000000000,1000000000000000), 36) credentials = bytearray((username+":s.whatsapp.net:").encode()) credentials.extend(password) if sys.version_info >= (3, 0): buf = lambda x: bytes(x, 'iso-8859-1') if type(x) is str else bytes(x) else: buf = buffer response = self.encode( self.md5( self.encode( self.md5( self.md5( buf ( credentials ) ) + (":" + nonce + ":" + cnonce).encode() ) ) + (":"+nonce+":" + WAContactsSyncAuth.nc+":" + cnonce + ":auth:").encode() + self.encode( self.md5(("AUTHENTICATE:"+WAContactsSyncAuth.digestUri).encode()) ))).decode() authField = WAContactsSyncAuth.authTemplate.format(auth_method = WAContactsSyncAuth.authMethod, username = username, realm = WAContactsSyncAuth.realm, nonce = nonce, cnonce = cnonce, nc= WAContactsSyncAuth.nc, digest_uri = WAContactsSyncAuth.digestUri, response = response) self.addHeaderField("Authorization", authField) self.pvars = ["message"] self.setParser(JSONResponseParser()) def md5(self, data): return md5(data).digest(); def getResponseDigest(self): pass def encode(self, inp): res = [] def _enc(n): if n < 10: return n + 48 return n + 87 for c in inp: if type(inp) is str: c = ord(c) if c < 0: c += 256 res.append(_enc(c >> 4)) res.append(_enc(c % 16)) return "".join(map(chr, res)).encode(); class WAContactsSyncQuery(WAContactsSyncAuth): def __init__(self, username, password, nonce, contacts): super(WAContactsSyncQuery, self).__init__(username, password, nonce) self.url = "sro.whatsapp.net/v2/sync/q" self.pvars = ["c"] self.addParam("ut", "all") #self.addParam("ut", "wa") self.addParam("t", "c") #self.addParam("t", "w") for c in contacts: self.addParam("u[]", c)
mandeepdhami/nova
refs/heads/master
nova/tests/unit/virt/libvirt/test_lvm.py
17
# Copyright 2012 NTT Data. All Rights Reserved. # Copyright 2012 Yahoo! Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import contextlib import mock from oslo_concurrency import processutils from oslo_config import cfg from nova import exception from nova import test from nova import utils from nova.virt.libvirt import lvm from nova.virt.libvirt import utils as libvirt_utils CONF = cfg.CONF class LvmTestCase(test.NoDBTestCase): def test_get_volume_size(self): executes = [] def fake_execute(*cmd, **kwargs): executes.append(cmd) return 123456789, None expected_commands = [('blockdev', '--getsize64', '/dev/foo')] self.stubs.Set(utils, 'execute', fake_execute) size = lvm.get_volume_size('/dev/foo') self.assertEqual(expected_commands, executes) self.assertEqual(size, 123456789) @mock.patch.object(utils, 'execute', side_effect=processutils.ProcessExecutionError( stderr=('blockdev: cannot open /dev/foo: ' 'No such device or address'))) def test_get_volume_size_not_found(self, mock_execute): self.assertRaises(exception.VolumeBDMPathNotFound, lvm.get_volume_size, '/dev/foo') @mock.patch.object(utils, 'execute', side_effect=processutils.ProcessExecutionError( stderr=('blockdev: cannot open /dev/foo: ' 'No such file or directory'))) def test_get_volume_size_not_found_file(self, mock_execute): self.assertRaises(exception.VolumeBDMPathNotFound, lvm.get_volume_size, '/dev/foo') @mock.patch.object(libvirt_utils, 'path_exists', return_value=True) @mock.patch.object(utils, 'execute', side_effect=processutils.ProcessExecutionError( stderr='blockdev: i am sad in other ways')) def test_get_volume_size_unexpectd_error(self, mock_execute, mock_path_exists): self.assertRaises(processutils.ProcessExecutionError, lvm.get_volume_size, '/dev/foo') def test_lvm_clear(self): def fake_lvm_size(path): return lvm_size def fake_execute(*cmd, **kwargs): executes.append(cmd) self.stubs.Set(lvm, 'get_volume_size', fake_lvm_size) self.stubs.Set(utils, 'execute', fake_execute) # Test the correct dd commands are run for various sizes lvm_size = 1 executes = [] expected_commands = [('dd', 'bs=1', 'if=/dev/zero', 'of=/dev/v1', 'seek=0', 'count=1', 'conv=fdatasync')] lvm.clear_volume('/dev/v1') self.assertEqual(expected_commands, executes) lvm_size = 1024 executes = [] expected_commands = [('dd', 'bs=1024', 'if=/dev/zero', 'of=/dev/v2', 'seek=0', 'count=1', 'conv=fdatasync')] lvm.clear_volume('/dev/v2') self.assertEqual(expected_commands, executes) lvm_size = 1025 executes = [] expected_commands = [('dd', 'bs=1024', 'if=/dev/zero', 'of=/dev/v3', 'seek=0', 'count=1', 'conv=fdatasync')] expected_commands += [('dd', 'bs=1', 'if=/dev/zero', 'of=/dev/v3', 'seek=1024', 'count=1', 'conv=fdatasync')] lvm.clear_volume('/dev/v3') self.assertEqual(expected_commands, executes) lvm_size = 1048576 executes = [] expected_commands = [('dd', 'bs=1048576', 'if=/dev/zero', 'of=/dev/v4', 'seek=0', 'count=1', 'oflag=direct')] lvm.clear_volume('/dev/v4') self.assertEqual(expected_commands, executes) lvm_size = 1048577 executes = [] expected_commands = [('dd', 'bs=1048576', 'if=/dev/zero', 'of=/dev/v5', 'seek=0', 'count=1', 'oflag=direct')] expected_commands += [('dd', 'bs=1', 'if=/dev/zero', 'of=/dev/v5', 'seek=1048576', 'count=1', 'conv=fdatasync')] lvm.clear_volume('/dev/v5') self.assertEqual(expected_commands, executes) lvm_size = 1234567 executes = [] expected_commands = [('dd', 'bs=1048576', 'if=/dev/zero', 'of=/dev/v6', 'seek=0', 'count=1', 'oflag=direct')] expected_commands += [('dd', 'bs=1024', 'if=/dev/zero', 'of=/dev/v6', 'seek=1024', 'count=181', 'conv=fdatasync')] expected_commands += [('dd', 'bs=1', 'if=/dev/zero', 'of=/dev/v6', 'seek=1233920', 'count=647', 'conv=fdatasync')] lvm.clear_volume('/dev/v6') self.assertEqual(expected_commands, executes) # Test volume_clear_size limits the size lvm_size = 10485761 CONF.set_override('volume_clear_size', '1', 'libvirt') executes = [] expected_commands = [('dd', 'bs=1048576', 'if=/dev/zero', 'of=/dev/v7', 'seek=0', 'count=1', 'oflag=direct')] lvm.clear_volume('/dev/v7') self.assertEqual(expected_commands, executes) CONF.set_override('volume_clear_size', '2', 'libvirt') lvm_size = 1048576 executes = [] expected_commands = [('dd', 'bs=1048576', 'if=/dev/zero', 'of=/dev/v9', 'seek=0', 'count=1', 'oflag=direct')] lvm.clear_volume('/dev/v9') self.assertEqual(expected_commands, executes) # Test volume_clear=shred CONF.set_override('volume_clear', 'shred', 'libvirt') CONF.set_override('volume_clear_size', '0', 'libvirt') lvm_size = 1048576 executes = [] expected_commands = [('shred', '-n3', '-s1048576', '/dev/va')] lvm.clear_volume('/dev/va') self.assertEqual(expected_commands, executes) CONF.set_override('volume_clear', 'shred', 'libvirt') CONF.set_override('volume_clear_size', '1', 'libvirt') lvm_size = 10485761 executes = [] expected_commands = [('shred', '-n3', '-s1048576', '/dev/vb')] lvm.clear_volume('/dev/vb') self.assertEqual(expected_commands, executes) # Test volume_clear=none does nothing CONF.set_override('volume_clear', 'none', 'libvirt') executes = [] expected_commands = [] lvm.clear_volume('/dev/vc') self.assertEqual(expected_commands, executes) @mock.patch.object(utils, 'execute', side_effect=processutils.ProcessExecutionError( stderr=('blockdev: cannot open /dev/foo: ' 'No such file or directory'))) def test_lvm_clear_ignore_lvm_not_found(self, mock_execute): lvm.clear_volume('/dev/foo') def test_fail_remove_all_logical_volumes(self): def fake_execute(*args, **kwargs): if 'vol2' in args: raise processutils.ProcessExecutionError('Error') with contextlib.nested( mock.patch.object(lvm, 'clear_volume'), mock.patch.object(libvirt_utils, 'execute', side_effect=fake_execute)) as (mock_clear, mock_execute): self.assertRaises(exception.VolumesNotRemoved, lvm.remove_volumes, ['vol1', 'vol2', 'vol3']) self.assertEqual(3, mock_execute.call_count)
FFMG/myoddweb.piger
refs/heads/master
monitor/api/python/Python-3.7.2/Lib/test/final_b.py
103
""" Fodder for module finalization tests in test_module. """ import shutil import test.final_a x = 'b' class C: def __del__(self): # Inspect module globals and builtins print("x =", x) print("final_a.x =", test.final_a.x) print("shutil.rmtree =", getattr(shutil.rmtree, '__name__', None)) print("len =", getattr(len, '__name__', None)) c = C() _underscored = C()
StrellaGroup/erpnext
refs/heads/develop
erpnext/hr/report/bank_remittance/bank_remittance.py
6
# Copyright (c) 2013, Frappe Technologies Pvt. Ltd. and contributors # For license information, please see license.txt from __future__ import unicode_literals import frappe from frappe.utils import formatdate import itertools from frappe import _, get_all def execute(filters=None): columns = [ { "label": _("Payroll Number"), "fieldtype": "Link", "fieldname": "payroll_no", "options": "Payroll Entry", "width": 150 }, { "label": _("Debit A/C Number"), "fieldtype": "Int", "fieldname": "debit_account", "hidden": 1, "width": 200 }, { "label": _("Payment Date"), "fieldtype": "Data", "fieldname": "payment_date", "width": 100 }, { "label": _("Employee Name"), "fieldtype": "Link", "fieldname": "employee_name", "options": "Employee", "width": 200 }, { "label": _("Bank Name"), "fieldtype": "Data", "fieldname": "bank_name", "width": 50 }, { "label": _("Employee A/C Number"), "fieldtype": "Int", "fieldname": "employee_account_no", "width": 50 }, { "label": _("IFSC Code"), "fieldtype": "Data", "fieldname": "bank_code", "width": 100 }, { "label": _("Currency"), "fieldtype": "Data", "fieldname": "currency", "width": 50 }, { "label": _("Net Salary Amount"), "fieldtype": "Currency", "options": "currency", "fieldname": "amount", "width": 100 } ] data = [] accounts = get_bank_accounts() payroll_entries = get_payroll_entries(accounts, filters) salary_slips = get_salary_slips(payroll_entries) get_emp_bank_ifsc_code(salary_slips) for salary in salary_slips: if salary.bank_name and salary.bank_account_no and salary.debit_acc_no and salary.status in ["Submitted", "Paid"]: row = { "payroll_no": salary.payroll_entry, "debit_account": salary.debit_acc_no, "payment_date": frappe.utils.formatdate(salary.modified.strftime('%Y-%m-%d')), "bank_name": salary.bank_name, "employee_account_no": salary.bank_account_no, "bank_code": salary.ifsc_code, "employee_name": salary.employee+": " + salary.employee_name, "currency": frappe.get_cached_value('Company', filters.company, 'default_currency'), "amount": salary.net_pay, } data.append(row) return columns, data def get_bank_accounts(): accounts = [d.name for d in get_all("Account", filters={"account_type": "Bank"})] return accounts def get_payroll_entries(accounts, filters): payroll_filter = [ ('payment_account', 'IN', accounts), ('number_of_employees', '>', 0), ('Company', '=', filters.company) ] if filters.to_date: payroll_filter.append(('posting_date', '<', filters.to_date)) if filters.from_date: payroll_filter.append(('posting_date', '>', filters.from_date)) entries = get_all("Payroll Entry", payroll_filter, ["name", "payment_account"]) payment_accounts = [d.payment_account for d in entries] set_company_account(payment_accounts, entries) return entries def get_salary_slips(payroll_entries): payroll = [d.name for d in payroll_entries] salary_slips = get_all("Salary Slip", filters = [("payroll_entry", "IN", payroll)], fields = ["modified", "net_pay", "bank_name", "bank_account_no", "payroll_entry", "employee", "employee_name", "status"] ) payroll_entry_map = {} for entry in payroll_entries: payroll_entry_map[entry.name] = entry # appending company debit accounts for slip in salary_slips: slip["debit_acc_no"] = payroll_entry_map[slip.payroll_entry]['company_account'] return salary_slips def get_emp_bank_ifsc_code(salary_slips): emp_names = [d.employee for d in salary_slips] ifsc_codes = get_all("Employee", [("name", "IN", emp_names)], ["ifsc_code", "name"]) ifsc_codes_map = {} for code in ifsc_codes: ifsc_codes_map[code.name] = code for slip in salary_slips: slip["ifsc_code"] = ifsc_codes_map[code.name]['ifsc_code'] return salary_slips def set_company_account(payment_accounts, payroll_entries): company_accounts = get_all("Bank Account", [("account", "in", payment_accounts)], ["account", "bank_account_no"]) company_accounts_map = {} for acc in company_accounts: company_accounts_map[acc.account] = acc for entry in payroll_entries: entry["company_account"] = company_accounts_map[entry.payment_account]['bank_account_no'] return payroll_entries
Nowheresly/odoo
refs/heads/8.0
addons/website_forum/controllers/__init__.py
4497
# -*- coding: utf-8 -*- import main
royorbs3/Leviathan-V1-Kernel-G925T
refs/heads/master
tools/perf/python/twatch.py
7370
#! /usr/bin/python # -*- python -*- # -*- coding: utf-8 -*- # twatch - Experimental use of the perf python interface # Copyright (C) 2011 Arnaldo Carvalho de Melo <acme@redhat.com> # # This application is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; version 2. # # This application is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # General Public License for more details. import perf def main(): cpus = perf.cpu_map() threads = perf.thread_map() evsel = perf.evsel(task = 1, comm = 1, mmap = 0, wakeup_events = 1, watermark = 1, sample_id_all = 1, sample_type = perf.SAMPLE_PERIOD | perf.SAMPLE_TID | perf.SAMPLE_CPU | perf.SAMPLE_TID) evsel.open(cpus = cpus, threads = threads); evlist = perf.evlist(cpus, threads) evlist.add(evsel) evlist.mmap() while True: evlist.poll(timeout = -1) for cpu in cpus: event = evlist.read_on_cpu(cpu) if not event: continue print "cpu: %2d, pid: %4d, tid: %4d" % (event.sample_cpu, event.sample_pid, event.sample_tid), print event if __name__ == '__main__': main()
pygeek/django
refs/heads/master
tests/regressiontests/bash_completion/management/commands/test_command.py
183
from optparse import make_option from django.core.management.base import BaseCommand class Command(BaseCommand): option_list = BaseCommand.option_list + ( make_option("--list", action="store_true", dest="list", help="Print all options"), ) def handle(self, *args, **options): pass
ecotg/Misc
refs/heads/master
Visions/for_360pi/spiders/__init__.py
1
""" Scrape: Visions.ca To run this script, in this directory, run 'scrapy crawl visions' in the terminal. For each category listed on the lefthand banner on the http://www.visions.ca/Default.aspx page, this script will extract the product details for one product. First, the spider will extract and follow the hrefs for all thirteen categories, see rule 1. Then for all the categories, apart from 'Bundles', the spider will find and follow href link for the first brand listed on the category pages' left hand menu, see rule 2. Once on the brand page, this spider will extract the details for the first product listed on that page. For the 'Bundles' category, due to the category page's different layout, the spider will extract the link for the first product listed on that page, follow that link, and then extract the product's details, see Rule 3. For each run of the spider, a JSON file and log file are created, containing the thirteen scraped products, one per category, and a log for the spider, respectively. Each of thirteen categories are listed as a field for their respective product. Script utilizes the Scrapy method, its xpath, ItemLoader and LinkExtractor classes to obtain the product data. """ from for_360pi.items import VisionsProduct from scrapy.selector import Selector from scrapy.contrib.loader import ItemLoader from scrapy.contrib.spiders import CrawlSpider, Rule from scrapy.contrib.linkextractors import LinkExtractor class VisionSpyder(CrawlSpider): name = 'visions' allowed_domains = ['visions.ca'] start_urls = ['http://www.visions.ca/Default.aspx'] # Store long xpaths as a string to aid clarity. xpath1 = ('//*[@id="mastermenu-container"]/ul[@id="mastermenu-startbtn"]' '/li/ul[@id="mastermenu-dropdown"]/li/a[starts-with(@href,' '"/Catalogue/")]') xpath2 = ('//*[@id="subcatemenu-container"]' '/div[@id="subcatemenu-brand-all"]/ul/li[1]') xpath3 = ('//*[@id="ctl00_tdMainPanel"]/div[contains(@class,' '"bundleItem")][1]//a[contains(@id, "BundleName")]') rules = (Rule(LinkExtractor(allow = ('/Catalogue/.*'), restrict_xpaths = (xpath1), deny_domains = ('ProductResults')),), Rule(LinkExtractor(restrict_xpaths = (xpath2)), callback = 'parse_by_brand'), Rule(LinkExtractor(restrict_xpaths = (xpath3)), callback = 'parse_by_product'),) def parse_by_brand(self, response): """ Except for the 'Bundles' page, for the first brand listed on each category page, extract the product details for the first listed product. """ selector = Selector(response) # Use the 'Bread Crumbs' attribute to compose the category path. self.crumb_xpath_1 = ('//*[@id="ctl00_pnlBreadCrumbs"]/a//text()') self.crumb_1 = selector.xpath(self.crumb_xpath_1).extract() self.crumb_xpath_2 = ('//*[@id="ctl00_pnlBreadCrumbs"]/span//text()') self.crumb_2 = selector.xpath(self.crumb_xpath_2).extract() self.category = ('/'.join(self.crumb_1).encode('utf-8') + '/' + '/'.join(self.crumb_2).encode('utf-8')) self.empty_page_xpath = ('//*[@id="ctl00_tdMainPanel"]' '/div/div[@id="ctl00_Content' 'PlaceHolder1_pnlNoRecords"]') if (selector.xpath(self.empty_page_xpath)): loader = ItemLoader(item = VisionsProduct(), response = response) self.empty_page = 'Empty Page/No Records' # set product details for an empty page loader.add_value('category', self.category) loader.add_value('product', self.empty_page) loader.add_value('price', self.empty_page) loader.add_value('availability', self.empty_page) else: # If not-empty, extract and load product details self.results_xpath = ('//*[contains(@class,' '"productresult-itembox")]') self.results = selector.xpath(self.results_xpath) loader = ItemLoader(item = VisionsProduct(), selector = self.results[0]) # Store long xpaths in dict to aid clarity self.field_xpaths = { 'product': ('div[contains(@class,' '"contentright")]/h2/a/font/text()'), 'price': ('div[contains(@class, "contentright")]' '/div/div/span[@class="price"]'), 'price_gif': ('div[contains(@class,"contentright")' ']/div/div[contains(@id, "AddToCart")]/a/img'), 'clearance_gif': ('div[contains(@class,' '"productresult-imagebox")]/div/div[contains' '(@style,"position:absolute; bottom")]/img' '[contains(@src, "final_clearance_' 'box.gif")]') } loader.add_value('category', self.category) loader.add_xpath('product', self.field_xpaths['product']) # Use the first listed price, which equals the sale price if # product on sale, else is the regular price. # For products without listed price, check for 'In Store' img # attribute to indicate price detail. try: loader.add_xpath('price', self.field_xpaths['price'], re = '\$[\d]*[,]*[\d]*\.[\d]*') except IndexError: if (self.results[0].xpath(self.field_xpaths['price_gif'])): loader.add_value('price', 'Available only In-Store') # Use the Final clearance gif to help determine product # availability. if (self.results[0].xpath(self.field_xpaths['clearance_gif'])): loader.add_value('availability', 'Limited Quantity/Clearance') else: loader.add_value('availability', 'Not Limited/Clearance Item') yield loader.load_item() def parse_by_product(self, response): """ For the 'Bundles' category, grab the product details for the first product listed. """ self.selector = Selector(response) self.results = self.selector.xpath('//*[@id="ctl00_tdMainPanel"]') loader = ItemLoader(item = VisionsProduct(), selector = self.results[0]) self.field_xpaths = { 'product': ('div[contains(@class, "catalogueTitle")]' '/h3/text()'), 'price': ('div[@id="ctl00_ContentPlaceHolder1_pnl' 'Bundle"]/div[@id="divProductDetails"]/div' '[contains(@class, "priceAddToCart")]/div[1]/span' '[contains(@id, "SalePrice")]/text()') } # Extract and load product details loader.add_xpath('product', self.field_xpaths['product']) loader.add_xpath('price', self.field_xpaths['price'], re = '\$[\d]*[,]*[\d]*\.[\d]*') loader.add_value('availability', 'Not Limited/Clearance Item') # Because it's an individual product page, manually set the category self.category = '/'.join(['Home', response.url.split('/')[4]]) loader.add_value('category', self.category) yield loader.load_item() def main(): VisionSpyder() if __name__ == '__main__': main()
the-zebulan/CodeWars
refs/heads/master
tests/beta_tests/test_separate_filename_from_extension.py
1
import unittest from katas.beta.separate_filename_from_extension import \ separate_filename_from_extension class SeparateFilenameFromExtensionTestCase(unittest.TestCase): def test_equal_1(self): self.assertEqual(separate_filename_from_extension( '/some/path/to/file.txt' ), ('/some/path/to/file', '.txt')) def test_equal_2(self): self.assertEqual(separate_filename_from_extension( '/some/path/.to/.file.txt' ), ('/some/path/.to/.file', '.txt')) def test_equal_3(self): self.assertEqual(separate_filename_from_extension( '/some/path/.to/.file.tar.gz' ), ('/some/path/.to/.file', '.tar.gz'))
Hao-Liu/avocado-vt
refs/heads/master
virttest/libvirt_xml/capability_xml.py
18
""" Module simplifying manipulation of XML described at http://libvirt.org/formatcaps.html """ from virttest import xml_utils from virttest.libvirt_xml import base, accessors, xcepts class CapabilityXML(base.LibvirtXMLBase): """ Handler of libvirt capabilities and nonspecific item operations. Properties: uuid: string of host uuid guest_capabilities: dict, read-only get: dict map from os type names to dict map from arch names """ # TODO: Add more __slots__ and accessors to get some useful stats # e.g. guest_count etc. __slots__ = ('uuid', 'guest_capabilities', 'cpu_count', 'arch', 'model', 'vendor', 'feature_list', 'power_management_list', 'cpu_topology', 'cells_topology') __schema_name__ = "capability" def __init__(self, virsh_instance=base.virsh): accessors.XMLElementText(property_name="uuid", libvirtxml=self, forbidden=['set', 'del'], parent_xpath='/host', tag_name='uuid') # This will skip self.get_guest_capabilities() defined below accessors.AllForbidden(property_name="guest_capabilities", libvirtxml=self) # This will skip self.get_cpu_count() defined below accessors.AllForbidden(property_name="cpu_count", libvirtxml=self) # The set action is for test. accessors.XMLElementText(property_name="arch", libvirtxml=self, forbidden=['del'], parent_xpath='/host/cpu', tag_name='arch') accessors.XMLElementText(property_name="model", libvirtxml=self, forbidden=['del'], parent_xpath='/host/cpu', tag_name='model') accessors.XMLElementText(property_name="vendor", libvirtxml=self, forbidden=['del'], parent_xpath='/host/cpu', tag_name='vendor') accessors.XMLElementDict(property_name="cpu_topology", libvirtxml=self, forbidden=['del'], parent_xpath='/host/cpu', tag_name='topology') accessors.XMLElementNest(property_name='cells_topology', libvirtxml=self, parent_xpath='/host', tag_name='topology', subclass=TopologyXML, subclass_dargs={ 'virsh_instance': virsh_instance}) # This will skip self.get_feature_list() defined below accessors.AllForbidden(property_name="feature_list", libvirtxml=self) # This will skip self.get_power_management_list() defined below accessors.AllForbidden(property_name="power_management_list", libvirtxml=self) super(CapabilityXML, self).__init__(virsh_instance) # calls set_xml accessor method self['xml'] = self.__dict_get__('virsh').capabilities() def get_guest_capabilities(self): """ Accessor method for guest_capabilities property (in __slots__). Return a guest capabilities dict in following schema: {<os_type>: {<arch name>: {'wordsize': '', 'emulator': '', 'machine': [<machine name>, ...], 'domaini_<type>': {'emulator': ''}}}} """ guest_capa = {} xmltreefile = self.__dict_get__('xml') for guest in xmltreefile.findall('guest'): os_type_name = guest.find('os_type').text # Multiple guest definitions can share same os_type (e.g. hvm, pvm) if os_type_name == 'xen': os_type_name = 'pv' guest_arch = guest_capa.get(os_type_name, {}) for arch in guest.findall('arch'): arch_name = arch.get('name') arch_prop = guest_arch.get(arch_name, {}) arch_prop['wordsize'] = arch.find('wordsize').text arch_prop['emulator'] = arch.find('emulator').text m_list = [] for machine in arch.findall('machine'): machine_text = machine.text # Don't add duplicate entries if not m_list.count(machine_text): m_list.append(machine_text) arch_prop['machine'] = m_list for domain in arch.findall('domain'): domain_name = "domain_" + domain.get('type') dom_prop = {} if domain.find('emulator') is not None: dom_prop['emulator'] = domain.find('emulator').text arch_prop[domain_name] = dom_prop guest_arch[arch_name] = arch_prop guest_capa[os_type_name] = guest_arch return guest_capa def get_power_management_list(self): """ Accessor method for power_management_list property (in __slots__) """ xmltreefile = self.__dict_get__('xml') pms = xmltreefile.find('host').find('power_management').getchildren() return [pm.tag for pm in pms] def get_feature_list(self): """ Accessor method for feature_list property (in __slots__) """ feature_list = [] # [<feature1>, <feature2>, ...] xmltreefile = self.__dict_get__('xml') for feature_node in xmltreefile.findall('/host/cpu/feature'): feature_list.append(feature_node) return feature_list def get_feature(self, num): """ Get a feature element from feature list by number :return: Feature element """ count = len(self.feature_list) try: num = int(num) return self.feature_list[num] except (ValueError, TypeError): raise xcepts.LibvirtXMLError("Invalid feature number %s" % num) except IndexError: raise xcepts.LibvirtXMLError("Only %d feature(s)" % count) def get_feature_name(self, num): """ Get assigned feature name :param num: Assigned feature number :return: Assigned feature name """ return self.get_feature(num).get('name') def get_cpu_count(self): """ Accessor method for cpu_count property (in __slots__) """ cpu_count = 0 xmltreefile = self.__dict_get__('xml') for cpus in xmltreefile.findall('/host/topology/cells/cell/cpus'): cpu_num = cpus.get('num') cpu_count += int(cpu_num) return cpu_count def remove_feature(self, num): """ Remove a assigned feature from xml :param num: Assigned feature number """ xmltreefile = self.__dict_get__('xml') feature_remove_node = self.get_feature(num) cpu_node = xmltreefile.find('/host/cpu') cpu_node.remove(feature_remove_node) def check_feature_name(self, name): """ Check feature name valid or not. :param name: The checked feature name :return: True if check pass """ sys_feature = [] cpu_xml_file = open('/proc/cpuinfo', 'r') for line in cpu_xml_file.readlines(): if line.find('flags') != -1: feature_names = line.split(':')[1].strip() sys_sub_feature = feature_names.split(' ') sys_feature = list(set(sys_feature + sys_sub_feature)) cpu_xml_file.close() return (name in sys_feature) def set_feature(self, num, value): """ Set a assigned feature value to xml :param num: Assigned feature number :param value: The feature name modified to """ feature_set_node = self.get_feature(num) feature_set_node.set('name', value) def add_feature(self, value): """ Add a feature Element to xml :param value: The added feature name """ xmltreefile = self.__dict_get__('xml') cpu_node = xmltreefile.find('/host/cpu') xml_utils.ElementTree.SubElement(cpu_node, 'feature', {'name': value}) class TopologyXML(base.LibvirtXMLBase): """ Handler of cells topology element in libvirt capabilities. Properties: num: string of node cell numbers cell: list of cpu dict """ __slots__ = ('num', 'cell') def __init__(self, virsh_instance=base.virsh): """ Create new cells topology XML instance """ accessors.XMLAttribute(property_name="num", libvirtxml=self, parent_xpath='/', tag_name='cells', attribute='num') accessors.AllForbidden(property_name="cell", libvirtxml=self) super(TopologyXML, self).__init__(virsh_instance) self.xml = self.__dict_get__('virsh').capabilities() self.xmltreefile.reroot("/host/topology") self.xmltreefile.write() def get_cell(self): """ Return CellXML instances list """ cell_list = [] for cell_node in self.xmltreefile.findall('/cells/cell'): xml_str = xml_utils.ElementTree.tostring( cell_node) new_cell = CellXML() new_cell.xml = xml_str cell_list.append(new_cell) return cell_list class CellXML(base.LibvirtXMLBase): """ Handler of cell element in libvirt capabilities. Properties: cell_id: string of node cell number id memory: int, memory size mem_unit: string of memory unit pages: list of pages dict sibling: list of sibling dict cpus_num: string of cpus number cpu: list of cpu dict """ __slots__ = ('cell_id', 'memory', 'mem_unit', 'pages', 'sibling', 'cpus_num', 'cpu') def __init__(self, virsh_instance=base.virsh): """ Create new cpus XML instance """ accessors.XMLAttribute(property_name="cell_id", libvirtxml=self, parent_xpath='/', tag_name='cell', attribute='id') accessors.XMLElementInt(property_name="memory", libvirtxml=self, parent_xpath='/', tag_name='memory') accessors.XMLAttribute(property_name="mem_unit", libvirtxml=self, parent_xpath='/', tag_name='memory', attribute='unit') accessors.XMLElementList(property_name="pages", libvirtxml=self, parent_xpath='/', marshal_from=self.marshal_from_pages, marshal_to=self.marshal_to_pages) accessors.XMLElementList(property_name="sibling", libvirtxml=self, parent_xpath='/distances', marshal_from=self.marshal_from_sibling, marshal_to=self.marshal_to_sibling) accessors.XMLAttribute(property_name="cpus_num", libvirtxml=self, parent_xpath='/', tag_name='cpus', attribute='num') accessors.XMLElementList(property_name="cpu", libvirtxml=self, parent_xpath='/cpus', marshal_from=self.marshal_from_cpu, marshal_to=self.marshal_to_cpu) super(CellXML, self).__init__(virsh_instance) self.xml = u"<cell></cell>" @staticmethod def marshal_from_pages(item, index, libvirtxml): """ Convert a dict to pages tag and attributes. """ del index del libvirtxml if not isinstance(item, dict): raise xcepts.LibvirtXMLError("Expected a dictionary of pages " "attributes, not a %s" % str(item)) return ('pages', dict(item)) @staticmethod def marshal_to_pages(tag, attr_dict, index, libvirtxml, text): """ Convert a pages tag and attributes to a dict. """ del index del libvirtxml if tag != 'pages': return None attr_dict['text'] = text return dict(attr_dict) @staticmethod def marshal_from_sibling(item, index, libvirtxml): """ Convert a dict to sibling tag and attributes. """ del index del libvirtxml if not isinstance(item, dict): raise xcepts.LibvirtXMLError("Expected a dictionary of sibling " "attributes, not a %s" % str(item)) return ('sibling', dict(item)) @staticmethod def marshal_to_sibling(tag, attr_dict, index, libvirtxml): """ Convert a sibling tag and attributes to a dict. """ del index del libvirtxml if tag != 'sibling': return None return dict(attr_dict) @staticmethod def marshal_from_cpu(item, index, libvirtxml): """ Convert a dict to cpu tag and attributes. """ del index del libvirtxml if not isinstance(item, dict): raise xcepts.LibvirtXMLError("Expected a dictionary of cpu " "attributes, not a %s" % str(item)) return ('cpu', dict(item)) @staticmethod def marshal_to_cpu(tag, attr_dict, index, libvirtxml): """ Convert a cpu tag and attributes to a dict. """ del index del libvirtxml if tag != 'cpu': return None return dict(attr_dict)
nikhilprathapani/python-for-android
refs/heads/master
python3-alpha/python3-src/Doc/includes/sqlite3/simple_tableprinter.py
96
import sqlite3 FIELD_MAX_WIDTH = 20 TABLE_NAME = 'people' SELECT = 'select * from %s order by age, name_last' % TABLE_NAME con = sqlite3.connect("mydb") cur = con.cursor() cur.execute(SELECT) # Print a header. for fieldDesc in cur.description: print(fieldDesc[0].ljust(FIELD_MAX_WIDTH), end=' ') print() # Finish the header with a newline. print('-' * 78) # For each row, print the value of each field left-justified within # the maximum possible width of that field. fieldIndices = range(len(cur.description)) for row in cur: for fieldIndex in fieldIndices: fieldValue = str(row[fieldIndex]) print(fieldValue.ljust(FIELD_MAX_WIDTH), end=' ') print() # Finish the row with a newline.
gautam1858/tensorflow
refs/heads/master
tensorflow/python/autograph/core/function_wrapping.py
21
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Support for wrapping converted functions bodies with auxiliary logic.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import contextlib from tensorflow.python.framework import ops @contextlib.contextmanager def function_scope(function_name): """Returns a context manager for the converted body of a function.""" with ops.name_scope(function_name): yield
goloveychuk/compose
refs/heads/master
compose/project.py
1
from __future__ import absolute_import from __future__ import unicode_literals import logging from functools import reduce from docker.errors import APIError from .config import ConfigurationError from .config import get_service_name_from_net from .const import DEFAULT_TIMEOUT from .const import LABEL_ONE_OFF from .const import LABEL_PROJECT from .const import LABEL_SERVICE from .container import Container from .legacy import check_for_legacy_containers from .service import ContainerNet from .service import ConvergenceStrategy from .service import Net from .service import Service from .service import ServiceNet from .utils import parallel_execute log = logging.getLogger(__name__) def sort_service_dicts(services): # Topological sort (Cormen/Tarjan algorithm). unmarked = services[:] temporary_marked = set() sorted_services = [] def get_service_names(links): return [link.split(':')[0] for link in links] def get_service_dependents(service_dict, services): name = service_dict['name'] return [ service for service in services if (name in get_service_names(service.get('links', [])) or name in service.get('volumes_from', []) or name == get_service_name_from_net(service.get('net'))) ] def visit(n): if n['name'] in temporary_marked: if n['name'] in get_service_names(n.get('links', [])): raise DependencyError('A service can not link to itself: %s' % n['name']) if n['name'] in n.get('volumes_from', []): raise DependencyError('A service can not mount itself as volume: %s' % n['name']) else: raise DependencyError('Circular import between %s' % ' and '.join(temporary_marked)) if n in unmarked: temporary_marked.add(n['name']) for m in get_service_dependents(n, services): visit(m) temporary_marked.remove(n['name']) unmarked.remove(n) sorted_services.insert(0, n) while unmarked: visit(unmarked[-1]) return sorted_services class Project(object): """ A collection of services. """ def __init__(self, name, services, client): self.name = name self.services = services self.client = client def labels(self, one_off=False): return [ '{0}={1}'.format(LABEL_PROJECT, self.name), '{0}={1}'.format(LABEL_ONE_OFF, "True" if one_off else "False"), ] @classmethod def from_dicts(cls, name, service_dicts, client): """ Construct a ServiceCollection from a list of dicts representing services. """ project = cls(name, [], client) for service_dict in sort_service_dicts(service_dicts): links = project.get_links(service_dict) volumes_from = project.get_volumes_from(service_dict) net = project.get_net(service_dict) project.services.append( Service( client=client, project=name, links=links, net=net, volumes_from=volumes_from, **service_dict)) return project @property def service_names(self): return [service.name for service in self.services] def get_service(self, name): """ Retrieve a service by name. Raises NoSuchService if the named service does not exist. """ for service in self.services: if service.name == name: return service raise NoSuchService(name) def validate_service_names(self, service_names): """ Validate that the given list of service names only contains valid services. Raises NoSuchService if one of the names is invalid. """ valid_names = self.service_names for name in service_names: if name not in valid_names: raise NoSuchService(name) def get_services(self, service_names=None, include_deps=False): """ Returns a list of this project's services filtered by the provided list of names, or all services if service_names is None or []. If include_deps is specified, returns a list including the dependencies for service_names, in order of dependency. Preserves the original order of self.services where possible, reordering as needed to resolve dependencies. Raises NoSuchService if any of the named services do not exist. """ if service_names is None or len(service_names) == 0: return self.get_services( service_names=self.service_names, include_deps=include_deps ) else: unsorted = [self.get_service(name) for name in service_names] services = [s for s in self.services if s in unsorted] if include_deps: services = reduce(self._inject_deps, services, []) uniques = [] [uniques.append(s) for s in services if s not in uniques] return uniques def get_links(self, service_dict): links = [] if 'links' in service_dict: for link in service_dict.get('links', []): if ':' in link: service_name, link_name = link.split(':', 1) else: service_name, link_name = link, None try: links.append((self.get_service(service_name), link_name)) except NoSuchService: raise ConfigurationError( 'Service "%s" has a link to service "%s" which does not ' 'exist.' % (service_dict['name'], service_name)) del service_dict['links'] return links def get_volumes_from(self, service_dict): volumes_from = [] if 'volumes_from' in service_dict: for volume_name in service_dict.get('volumes_from', []): try: service = self.get_service(volume_name) volumes_from.append(service) except NoSuchService: try: container = Container.from_id(self.client, volume_name) volumes_from.append(container) except APIError: raise ConfigurationError( 'Service "%s" mounts volumes from "%s", which is ' 'not the name of a service or container.' % ( service_dict['name'], volume_name)) del service_dict['volumes_from'] return volumes_from def get_net(self, service_dict): net = service_dict.pop('net', None) if not net: return Net(None) net_name = get_service_name_from_net(net) if not net_name: return Net(net) try: return ServiceNet(self.get_service(net_name)) except NoSuchService: pass try: return ContainerNet(Container.from_id(self.client, net_name)) except APIError: raise ConfigurationError( 'Service "%s" is trying to use the network of "%s", ' 'which is not the name of a service or container.' % ( service_dict['name'], net_name)) def start(self, service_names=None, **options): for service in self.get_services(service_names): service.start(**options) def stop(self, service_names=None, **options): parallel_execute( objects=self.containers(service_names), obj_callable=lambda c: c.stop(**options), msg_index=lambda c: c.name, msg="Stopping" ) def pause(self, service_names=None, **options): for service in reversed(self.get_services(service_names)): service.pause(**options) def unpause(self, service_names=None, **options): for service in self.get_services(service_names): service.unpause(**options) def kill(self, service_names=None, **options): parallel_execute( objects=self.containers(service_names), obj_callable=lambda c: c.kill(**options), msg_index=lambda c: c.name, msg="Killing" ) def remove_stopped(self, service_names=None, **options): all_containers = self.containers(service_names, stopped=True) stopped_containers = [c for c in all_containers if not c.is_running] parallel_execute( objects=stopped_containers, obj_callable=lambda c: c.remove(**options), msg_index=lambda c: c.name, msg="Removing" ) def restart(self, service_names=None, **options): for service in self.get_services(service_names): service.restart(**options) def build(self, service_names=None, no_cache=False, pull=False, version=None): for service in self.get_services(service_names): if service.can_be_built(): if version is not None: service.put_version(version) service.build(no_cache, pull) else: log.info('%s uses an image, skipping' % service.name) def up(self, service_names=None, start_deps=True, strategy=ConvergenceStrategy.changed, do_build=True, timeout=DEFAULT_TIMEOUT, version=None): services = self.get_services(service_names, include_deps=start_deps) if version is not None: for service in services: service.put_version(version) for service in services: service.remove_duplicate_containers() plans = self._get_convergence_plans(services, strategy) return [ container for service in services for container in service.execute_convergence_plan( plans[service.name], do_build=do_build, timeout=timeout ) ] def _get_convergence_plans(self, services, strategy): plans = {} for service in services: updated_dependencies = [ name for name in service.get_dependency_names() if name in plans and plans[name].action == 'recreate' ] if updated_dependencies and strategy.allows_recreate: log.debug('%s has upstream changes (%s)', service.name, ", ".join(updated_dependencies)) plan = service.convergence_plan(ConvergenceStrategy.always) else: plan = service.convergence_plan(strategy) plans[service.name] = plan return plans def pull(self, service_names=None, ignore_pull_failures=False): for service in self.get_services(service_names, include_deps=True): service.pull(ignore_pull_failures) def containers(self, service_names=None, stopped=False, one_off=False): if service_names: self.validate_service_names(service_names) else: service_names = self.service_names containers = list(filter(None, [ Container.from_ps(self.client, container) for container in self.client.containers( all=stopped, filters={'label': self.labels(one_off=one_off)})])) def matches_service_names(container): return container.labels.get(LABEL_SERVICE) in service_names if not containers: check_for_legacy_containers( self.client, self.name, self.service_names, ) return [c for c in containers if matches_service_names(c)] def _inject_deps(self, acc, service): dep_names = service.get_dependency_names() if len(dep_names) > 0: dep_services = self.get_services( service_names=list(set(dep_names)), include_deps=True ) else: dep_services = [] dep_services.append(service) return acc + dep_services class NoSuchService(Exception): def __init__(self, name): self.name = name self.msg = "No such service: %s" % self.name def __str__(self): return self.msg class DependencyError(ConfigurationError): pass
jffernandez/kivy
refs/heads/master
examples/widgets/textinput.py
81
''' Textinput tests =============== This test is used to demonstrate virtual keyboard according to current configuration. Run this test as:: # use dock virtual keyboard (one instance) python textinput.py -c kivy:keyboard_mode:dock # use multi users virtual keyboard (multiples instance) python textinput.py -c kivy:keyboard_mode:multi # use system keyboard (one instance) python textinput.py -c kivy:keyboard_mode:system # use automatic detection from current platform python textinput.py -c kivy:keyboard_mode: ''' import kivy kivy.require('1.0.8') from kivy.core.window import Window from kivy.uix.textinput import TextInput from kivy.uix.floatlayout import FloatLayout from kivy.uix.scatter import Scatter from kivy.uix.button import Button from kivy.uix.label import Label from kivy.config import Config from kivy.base import runTouchApp if __name__ == '__main__': root = FloatLayout() # create a button to release everything def release_all_keyboard(*l): Window.release_all_keyboards() btn = Button(text='Release\nall\nkeyboards', size_hint=(None, None), halign='center') btn.bind(on_release=release_all_keyboard) root.add_widget(btn) # show current configuration lbl = 'Configuration keyboard_mode is %r, keyboard_layout is %r' % ( Config.get('kivy', 'keyboard_mode'), Config.get('kivy', 'keyboard_layout')) label = Label(text=lbl, size_hint_y=None, height=50, pos_hint={'top': 1}) root.add_widget(label) s = Scatter(size_hint=(None, None), pos=(300, 300)) s.add_widget(TextInput(size_hint=(None, None), size=(100, 50))) root.add_widget(s) s = Scatter(size_hint=(None, None), pos=(400, 300), rotation=45) s.add_widget(TextInput(size_hint=(None, None), size=(100, 50))) root.add_widget(s) runTouchApp(root)
TeamExodus/external_chromium_org
refs/heads/EXODUS-5.1
build/android/pylib/junit/test_runner.py
26
# Copyright 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import os from pylib import cmd_helper from pylib import constants class JavaTestRunner(object): """Runs java tests on the host.""" def __init__(self, options): self._package_filter = options.package_filter self._runner_filter = options.runner_filter self._sdk_version = options.sdk_version self._test_filter = options.test_filter self._test_suite = options.test_suite def SetUp(self): pass def RunTest(self, _test): """Runs junit tests from |self._test_suite|.""" command = ['java', '-jar', os.path.join(constants.GetOutDirectory(), 'lib.java', '%s.jar' % self._test_suite)] if self._test_filter: command.extend(['-gtest-filter', self._test_filter]) if self._package_filter: command.extend(['-package-filter', self._package_filter]) if self._runner_filter: command.extend(['-runner-filter', self._runner_filter]) if self._sdk_version: command.extend(['-sdk-version', self._sdk_version]) return cmd_helper.RunCmd(command) def TearDown(self): pass
dreamsxin/kbengine
refs/heads/master
kbe/res/scripts/common/Lib/test/audiotests.py
72
from test.support import findfile, TESTFN, unlink import unittest import array import io import pickle import sys class UnseekableIO(io.FileIO): def tell(self): raise io.UnsupportedOperation def seek(self, *args, **kwargs): raise io.UnsupportedOperation class AudioTests: close_fd = False def setUp(self): self.f = self.fout = None def tearDown(self): if self.f is not None: self.f.close() if self.fout is not None: self.fout.close() unlink(TESTFN) def check_params(self, f, nchannels, sampwidth, framerate, nframes, comptype, compname): self.assertEqual(f.getnchannels(), nchannels) self.assertEqual(f.getsampwidth(), sampwidth) self.assertEqual(f.getframerate(), framerate) self.assertEqual(f.getnframes(), nframes) self.assertEqual(f.getcomptype(), comptype) self.assertEqual(f.getcompname(), compname) params = f.getparams() self.assertEqual(params, (nchannels, sampwidth, framerate, nframes, comptype, compname)) self.assertEqual(params.nchannels, nchannels) self.assertEqual(params.sampwidth, sampwidth) self.assertEqual(params.framerate, framerate) self.assertEqual(params.nframes, nframes) self.assertEqual(params.comptype, comptype) self.assertEqual(params.compname, compname) dump = pickle.dumps(params) self.assertEqual(pickle.loads(dump), params) class AudioWriteTests(AudioTests): def create_file(self, testfile): f = self.fout = self.module.open(testfile, 'wb') f.setnchannels(self.nchannels) f.setsampwidth(self.sampwidth) f.setframerate(self.framerate) f.setcomptype(self.comptype, self.compname) return f def check_file(self, testfile, nframes, frames): with self.module.open(testfile, 'rb') as f: self.assertEqual(f.getnchannels(), self.nchannels) self.assertEqual(f.getsampwidth(), self.sampwidth) self.assertEqual(f.getframerate(), self.framerate) self.assertEqual(f.getnframes(), nframes) self.assertEqual(f.readframes(nframes), frames) def test_write_params(self): f = self.create_file(TESTFN) f.setnframes(self.nframes) f.writeframes(self.frames) self.check_params(f, self.nchannels, self.sampwidth, self.framerate, self.nframes, self.comptype, self.compname) f.close() def test_write_context_manager_calls_close(self): # Close checks for a minimum header and will raise an error # if it is not set, so this proves that close is called. with self.assertRaises(self.module.Error): with self.module.open(TESTFN, 'wb'): pass with self.assertRaises(self.module.Error): with open(TESTFN, 'wb') as testfile: with self.module.open(testfile): pass def test_context_manager_with_open_file(self): with open(TESTFN, 'wb') as testfile: with self.module.open(testfile) as f: f.setnchannels(self.nchannels) f.setsampwidth(self.sampwidth) f.setframerate(self.framerate) f.setcomptype(self.comptype, self.compname) self.assertEqual(testfile.closed, self.close_fd) with open(TESTFN, 'rb') as testfile: with self.module.open(testfile) as f: self.assertFalse(f.getfp().closed) params = f.getparams() self.assertEqual(params.nchannels, self.nchannels) self.assertEqual(params.sampwidth, self.sampwidth) self.assertEqual(params.framerate, self.framerate) if not self.close_fd: self.assertIsNone(f.getfp()) self.assertEqual(testfile.closed, self.close_fd) def test_context_manager_with_filename(self): # If the file doesn't get closed, this test won't fail, but it will # produce a resource leak warning. with self.module.open(TESTFN, 'wb') as f: f.setnchannels(self.nchannels) f.setsampwidth(self.sampwidth) f.setframerate(self.framerate) f.setcomptype(self.comptype, self.compname) with self.module.open(TESTFN) as f: self.assertFalse(f.getfp().closed) params = f.getparams() self.assertEqual(params.nchannels, self.nchannels) self.assertEqual(params.sampwidth, self.sampwidth) self.assertEqual(params.framerate, self.framerate) if not self.close_fd: self.assertIsNone(f.getfp()) def test_write(self): f = self.create_file(TESTFN) f.setnframes(self.nframes) f.writeframes(self.frames) f.close() self.check_file(TESTFN, self.nframes, self.frames) def test_write_bytearray(self): f = self.create_file(TESTFN) f.setnframes(self.nframes) f.writeframes(bytearray(self.frames)) f.close() self.check_file(TESTFN, self.nframes, self.frames) def test_write_array(self): f = self.create_file(TESTFN) f.setnframes(self.nframes) f.writeframes(array.array('h', self.frames)) f.close() self.check_file(TESTFN, self.nframes, self.frames) def test_write_memoryview(self): f = self.create_file(TESTFN) f.setnframes(self.nframes) f.writeframes(memoryview(self.frames)) f.close() self.check_file(TESTFN, self.nframes, self.frames) def test_incompleted_write(self): with open(TESTFN, 'wb') as testfile: testfile.write(b'ababagalamaga') f = self.create_file(testfile) f.setnframes(self.nframes + 1) f.writeframes(self.frames) f.close() with open(TESTFN, 'rb') as testfile: self.assertEqual(testfile.read(13), b'ababagalamaga') self.check_file(testfile, self.nframes, self.frames) def test_multiple_writes(self): with open(TESTFN, 'wb') as testfile: testfile.write(b'ababagalamaga') f = self.create_file(testfile) f.setnframes(self.nframes) framesize = self.nchannels * self.sampwidth f.writeframes(self.frames[:-framesize]) f.writeframes(self.frames[-framesize:]) f.close() with open(TESTFN, 'rb') as testfile: self.assertEqual(testfile.read(13), b'ababagalamaga') self.check_file(testfile, self.nframes, self.frames) def test_overflowed_write(self): with open(TESTFN, 'wb') as testfile: testfile.write(b'ababagalamaga') f = self.create_file(testfile) f.setnframes(self.nframes - 1) f.writeframes(self.frames) f.close() with open(TESTFN, 'rb') as testfile: self.assertEqual(testfile.read(13), b'ababagalamaga') self.check_file(testfile, self.nframes, self.frames) def test_unseekable_read(self): with self.create_file(TESTFN) as f: f.setnframes(self.nframes) f.writeframes(self.frames) with UnseekableIO(TESTFN, 'rb') as testfile: self.check_file(testfile, self.nframes, self.frames) def test_unseekable_write(self): with UnseekableIO(TESTFN, 'wb') as testfile: with self.create_file(testfile) as f: f.setnframes(self.nframes) f.writeframes(self.frames) self.check_file(TESTFN, self.nframes, self.frames) def test_unseekable_incompleted_write(self): with UnseekableIO(TESTFN, 'wb') as testfile: testfile.write(b'ababagalamaga') f = self.create_file(testfile) f.setnframes(self.nframes + 1) try: f.writeframes(self.frames) except OSError: pass try: f.close() except OSError: pass with open(TESTFN, 'rb') as testfile: self.assertEqual(testfile.read(13), b'ababagalamaga') self.check_file(testfile, self.nframes + 1, self.frames) def test_unseekable_overflowed_write(self): with UnseekableIO(TESTFN, 'wb') as testfile: testfile.write(b'ababagalamaga') f = self.create_file(testfile) f.setnframes(self.nframes - 1) try: f.writeframes(self.frames) except OSError: pass try: f.close() except OSError: pass with open(TESTFN, 'rb') as testfile: self.assertEqual(testfile.read(13), b'ababagalamaga') framesize = self.nchannels * self.sampwidth self.check_file(testfile, self.nframes - 1, self.frames[:-framesize]) class AudioTestsWithSourceFile(AudioTests): @classmethod def setUpClass(cls): cls.sndfilepath = findfile(cls.sndfilename, subdir='audiodata') def test_read_params(self): f = self.f = self.module.open(self.sndfilepath) #self.assertEqual(f.getfp().name, self.sndfilepath) self.check_params(f, self.nchannels, self.sampwidth, self.framerate, self.sndfilenframes, self.comptype, self.compname) def test_close(self): with open(self.sndfilepath, 'rb') as testfile: f = self.f = self.module.open(testfile) self.assertFalse(testfile.closed) f.close() self.assertEqual(testfile.closed, self.close_fd) with open(TESTFN, 'wb') as testfile: fout = self.fout = self.module.open(testfile, 'wb') self.assertFalse(testfile.closed) with self.assertRaises(self.module.Error): fout.close() self.assertEqual(testfile.closed, self.close_fd) fout.close() # do nothing def test_read(self): framesize = self.nchannels * self.sampwidth chunk1 = self.frames[:2 * framesize] chunk2 = self.frames[2 * framesize: 4 * framesize] f = self.f = self.module.open(self.sndfilepath) self.assertEqual(f.readframes(0), b'') self.assertEqual(f.tell(), 0) self.assertEqual(f.readframes(2), chunk1) f.rewind() pos0 = f.tell() self.assertEqual(pos0, 0) self.assertEqual(f.readframes(2), chunk1) pos2 = f.tell() self.assertEqual(pos2, 2) self.assertEqual(f.readframes(2), chunk2) f.setpos(pos2) self.assertEqual(f.readframes(2), chunk2) f.setpos(pos0) self.assertEqual(f.readframes(2), chunk1) with self.assertRaises(self.module.Error): f.setpos(-1) with self.assertRaises(self.module.Error): f.setpos(f.getnframes() + 1) def test_copy(self): f = self.f = self.module.open(self.sndfilepath) fout = self.fout = self.module.open(TESTFN, 'wb') fout.setparams(f.getparams()) i = 0 n = f.getnframes() while n > 0: i += 1 fout.writeframes(f.readframes(i)) n -= i fout.close() fout = self.fout = self.module.open(TESTFN, 'rb') f.rewind() self.assertEqual(f.getparams(), fout.getparams()) self.assertEqual(f.readframes(f.getnframes()), fout.readframes(fout.getnframes())) def test_read_not_from_start(self): with open(TESTFN, 'wb') as testfile: testfile.write(b'ababagalamaga') with open(self.sndfilepath, 'rb') as f: testfile.write(f.read()) with open(TESTFN, 'rb') as testfile: self.assertEqual(testfile.read(13), b'ababagalamaga') with self.module.open(testfile, 'rb') as f: self.assertEqual(f.getnchannels(), self.nchannels) self.assertEqual(f.getsampwidth(), self.sampwidth) self.assertEqual(f.getframerate(), self.framerate) self.assertEqual(f.getnframes(), self.sndfilenframes) self.assertEqual(f.readframes(self.nframes), self.frames)
osungjin/livechat
refs/heads/master
livechat_app/hello_gae/handlers.py
1
# -*- coding: utf-8 -*- from flask import Blueprint from flask import render_template from flask import redirect, request import pdb hello_gae = Blueprint('hello_gae', __name__) livechat = Blueprint('livechat', __name__) @hello_gae.route('/') def login(): return render_template("login.html") @livechat.route('/') def chat(): name = request.args['id'] return render_template("liveChat.html",name=str(name))
chirilo/kuma
refs/heads/master
kuma/demos/models.py
5
from hashlib import md5 import operator from os import makedirs from os.path import basename, dirname, isdir, join from shutil import rmtree, copyfileobj import re from time import time import zipfile import magic from django.conf import settings from django.core.exceptions import ValidationError from django.core.files.storage import FileSystemStorage from django.db import models from django.db.models import Q from django.db.models.fields.files import FieldFile, ImageFieldFile from django.template.defaultfilters import filesizeformat from django.utils.text import slugify from django.utils.translation import ugettext_lazy as _ from constance import config from constance.admin import FIELDS from django.utils.functional import lazy from kuma.actioncounters.fields import ActionCounterField from kuma.core.managers import NamespacedTaggableManager from kuma.core.urlresolvers import reverse from kuma.core.utils import generate_filename_and_delete_previous from . import challenge_utils, DEMO_LICENSES, scale_image from .embed import VideoEmbedURLField SCREENSHOT_MAXW = getattr(settings, 'DEMO_SCREENSHOT_MAX_WIDTH', 480) SCREENSHOT_MAXH = getattr(settings, 'DEMO_SCREENSHOT_MAX_HEIGHT', 360) THUMBNAIL_MAXW = getattr(settings, 'DEMO_THUMBNAIL_MAX_WIDTH', 200) THUMBNAIL_MAXH = getattr(settings, 'DEMO_THUMBNAIL_MAX_HEIGHT', 150) # Set up a file system for demo uploads that can be kept separate from the rest # of /media if necessary. Lots of hackery here to ensure a set of sensible # defaults are tried. DEMO_UPLOADS_ROOT = getattr( settings, 'DEMO_UPLOADS_ROOT', '%s/uploads/demos' % getattr(settings, 'MEDIA_ROOT', 'media')) DEMO_UPLOADS_URL = getattr( settings, 'DEMO_UPLOADS_URL', '%s/uploads/demos' % getattr(settings, 'MEDIA_URL', '/media')) demo_uploads_fs = FileSystemStorage(location=DEMO_UPLOADS_ROOT, base_url=DEMO_UPLOADS_URL) DEMO_MIMETYPE_BLACKLIST = getattr(settings, 'DEMO_FILETYPE_BLACKLIST', [ 'application/msword', 'application/pdf', 'application/postscript', 'application/vnd.lotus-wordpro', 'application/vnd.ms-cab-compressed', 'application/vnd.ms-excel', 'application/vnd.ms-tnef', 'application/vnd.oasis.opendocument.text', 'application/vnd.symbian.install', 'application/x-123', 'application/x-arc', 'application/x-archive', 'application/x-arj', 'application/x-bittorrent', 'application/x-bzip2', 'application/x-compress', 'application/x-debian-package', 'application/x-dosexec', 'application/x-executable', 'application/x-gzip', 'application/x-iso9660-image', 'application/x-java-applet', 'application/x-java-jce-keystore', 'application/x-java-keystore', 'application/x-java-pack200', 'application/x-lha', 'application/x-lharc', 'application/x-lzip', 'application/x-msaccess', 'application/x-rar', 'application/x-rpm', 'application/x-sc', 'application/x-setupscript.', 'application/x-sharedlib', 'application/x-shockwave-flash', 'application/x-stuffit', 'application/x-tar', 'application/x-zip', 'application/x-xz', 'application/x-zoo', 'application/xml-sitemap', 'application/zip', 'model/vrml', 'model/x3d', 'text/x-msdos-batch', 'text/x-perl', 'text/x-php', ]) LAZY_CONSTANCE_TYPES = list(FIELDS.keys()) LAZY_CONSTANCE_TYPES.remove(unicode) # because we already have str in the list def _config(name, default=None): """ Just a silly wrapper arround the constance's config object. """ return getattr(config, name, default) """ A function to use constance's config object in an environment in which one requires lazy values such a model field parameters. E.g. something that is a pretty stupid idea but should show the risk as well:: class Entry(models.Model): title = models.CharField(max_length=config_lazy('ENTRY_MAX_LENGTH')) .. where ``ENTRY_MAX_LENGTH`` is the name of the config value. """ config_lazy = lazy(_config, *LAZY_CONSTANCE_TYPES) def get_root_for_submission(instance): """Build a root path for demo submission files""" username = instance.creator.username return join(username[0], username[1], username, md5(instance.slug).hexdigest()) def screenshot_upload_to(instance, filename, field_filename): base = get_root_for_submission(instance) filename = '%s_%s' % (int(time()), field_filename) return join(base, filename) def upload_screenshot_1(instance, filename): return screenshot_upload_to(instance, filename, 'screenshot_1.png') def upload_screenshot_2(instance, filename): return screenshot_upload_to(instance, filename, 'screenshot_2.png') def upload_screenshot_3(instance, filename): return screenshot_upload_to(instance, filename, 'screenshot_3.png') def upload_screenshot_4(instance, filename): return screenshot_upload_to(instance, filename, 'screenshot_4.png') def upload_screenshot_5(instance, filename): return screenshot_upload_to(instance, filename, 'screenshot_5.png') def demo_package_upload_to(instance, filename): base = get_root_for_submission(instance) filename = '%s_%s_%s' % (instance.slug[:20], int(time()), 'demo_package.zip') return join(base, filename) class ReplacingFieldZipFile(FieldFile): def delete(self, save=True): # Delete any unpacked zip file, if found. new_root_dir = self.path.replace('.zip', '') if isdir(new_root_dir): rmtree(new_root_dir) return super(ReplacingFieldZipFile, self).delete(save) def save(self, name, content, save=True): new_filename = generate_filename_and_delete_previous(self, name) super(ReplacingFieldZipFile, self).save(new_filename, content, save) def _get_size(self): """Override FieldFile size property to return 0 in case of a missing file.""" try: return super(ReplacingFieldZipFile, self)._get_size() except OSError: return 0 size = property(_get_size) class ReplacingZipFileField(models.FileField): # TODO:liberate """This field causes an uploaded file to replace an existing one on disk.""" attr_class = ReplacingFieldZipFile def __init__(self, *args, **kwargs): self.max_upload_size = kwargs.pop('max_upload_size', 5) super(ReplacingZipFileField, self).__init__(*args, **kwargs) def clean(self, *args, **kwargs): data = super(ReplacingZipFileField, self).clean(*args, **kwargs) file = data.file try: if file._size > self.max_upload_size: raise ValidationError( _('Please keep filesize under %s. Current filesize %s') % (filesizeformat(self.max_upload_size), filesizeformat(file._size)) ) except AttributeError: pass return data class ReplacingImageWithThumbFieldFile(ImageFieldFile): def thumbnail_name(self): # HACK: This works, but I'm not proud of it if not self.name: return '' parts = self.name.rsplit('.', 1) return ''.join((parts[0], '_thumb', '.', parts[1])) def thumbnail_url(self): if not self.url: return '' # HACK: Use legacy thumbnail URL, if new-style file missing. DEV = getattr(settings, 'DEV', False) if not DEV and not self.storage.exists(self.thumbnail_name()): return self.url.replace('screenshot', 'screenshot_thumb') # HACK: This works, but I'm not proud of it parts = self.url.rsplit('.', 1) return ''.join((parts[0], '_thumb', '.', parts[1])) def delete(self, save=True): # Delete any associated thumbnail image before deleting primary t_name = self.thumbnail_name() if t_name: self.storage.delete(t_name) return super(ImageFieldFile, self).delete(save) def save(self, name, content, save=True): new_filename = generate_filename_and_delete_previous(self, name) super(ImageFieldFile, self).save(new_filename, content, save) # Create associated scaled thumbnail image t_name = self.thumbnail_name() if t_name: thumb_file = scale_image( self.storage.open(new_filename), (self.field.thumb_max_width, self.field.thumb_max_height)) self.storage.save(t_name, thumb_file) class ReplacingImageWithThumbField(models.ImageField): # TODO:liberate """This field causes an uploaded file to replace an existing one on disk.""" attr_class = ReplacingImageWithThumbFieldFile def __init__(self, *args, **kwargs): self.full_max_width = kwargs.pop("full_max_width", SCREENSHOT_MAXW) self.full_max_height = kwargs.pop("full_max_height", SCREENSHOT_MAXH) self.thumb_max_width = kwargs.pop("thumb_max_width", THUMBNAIL_MAXW) self.thumb_max_height = kwargs.pop("thumb_max_height", THUMBNAIL_MAXH) super(ReplacingImageWithThumbField, self).__init__(*args, **kwargs) def clean(self, *args, **kwargs): data = super(ReplacingImageWithThumbField, self).clean(*args, **kwargs) # Scale the input image down to maximum full size. scaled_file = scale_image( data.file, (self.full_max_width, self.full_max_height)) if not scaled_file: raise ValidationError(_('Cannot process image')) data.file = scaled_file return data class SubmissionManager(models.Manager): """Manager for Submission objects""" def get_by_natural_key(self, slug): return self.get(slug=slug) # never show censored submissions def get_queryset(self): return super(SubmissionManager, self).get_queryset().exclude(censored=True) # TODO: Make these search functions into a mixin? # See: http://www.julienphalip.com/blog/2008/08/16/adding-search-django-site-snap/ def _normalize_query(self, query_string, findterms=re.compile(r'"([^"]+)"|(\S+)').findall, normspace=re.compile(r'\s{2,}').sub): ''' Splits the query string in invidual keywords, getting rid of unecessary spaces and grouping quoted words together. Example: >>> _normalize_query(' some random words "with quotes " and spaces') ['some', 'random', 'words', 'with quotes', 'and', 'spaces'] ''' return [normspace(' ', (t[0] or t[1]).strip()) for t in findterms(query_string)] # See: http://www.julienphalip.com/blog/2008/08/16/adding-search-django-site-snap/ def _get_query(self, query_string, search_fields): ''' Returns a query, that is a combination of Q objects. That combination aims to search keywords within a model by testing the given search fields. ''' query = None # Query to search for every search term terms = self._normalize_query(query_string) for term in terms: or_query = None # Query to search for a given term in each field for field_name in search_fields: q = Q(**{"%s__icontains" % field_name: term}) if or_query is None: or_query = q else: or_query = or_query | q if query is None: query = or_query else: query = query & or_query return query def search(self, query_string, sort): """Quick and dirty keyword search on submissions""" # TODO: Someday, replace this with a real search engine strip_qs = query_string.strip() if not strip_qs: return self.all_sorted(sort).order_by('-modified') else: query = self._get_query(strip_qs, ['title', 'summary', 'description']) return self.all_sorted(sort).filter(query).order_by('-modified') def all_sorted(self, sort=None, max=5): """Apply to .all() one of the sort orders supported for views""" queryset = self.all() if sort == 'launches': return queryset.order_by('-launches_total') elif sort == 'likes': return queryset.order_by('-likes_total') elif sort == 'upandcoming': return queryset.order_by('-likes_recent', '-launches_recent') elif sort == 'recentfeatured': return (queryset.filter(featured=True) .exclude(hidden=True) .order_by('-modified')[:max]) else: return queryset.order_by('-created') class Submission(models.Model): """Representation of a demo submission""" objects = SubmissionManager() admin_manager = models.Manager() title = models.CharField( _("what is your demo's name?"), max_length=255, blank=False, unique=True) slug = models.SlugField( _("slug"), blank=False, unique=True, max_length=50) summary = models.CharField( _("describe your demo in one line"), max_length=255, blank=False) description = models.TextField( _("describe your demo in more detail (optional)"), blank=True) featured = models.BooleanField(default=False) hidden = models.BooleanField( _("Hide this demo from others?"), default=False) censored = models.BooleanField(default=False) censored_url = models.URLField( _("Redirect URL for censorship."), blank=True, null=True) navbar_optout = models.BooleanField( _('control how your demo is launched'), choices=( (True, _('Disable navigation bar, launch demo in a new window')), (False, _('Use navigation bar, display demo in <iframe>')) ), default=False) # FIXME: remove since it's unneeded comments_total = models.PositiveIntegerField(default=0) launches = ActionCounterField() likes = ActionCounterField() taggit_tags = NamespacedTaggableManager(blank=True) screenshot_1 = ReplacingImageWithThumbField( _('Screenshot #1'), max_length=255, storage=demo_uploads_fs, upload_to=upload_screenshot_1, blank=False) screenshot_2 = ReplacingImageWithThumbField( _('Screenshot #2'), max_length=255, storage=demo_uploads_fs, upload_to=upload_screenshot_2, blank=True) screenshot_3 = ReplacingImageWithThumbField( _('Screenshot #3'), max_length=255, storage=demo_uploads_fs, upload_to=upload_screenshot_3, blank=True) screenshot_4 = ReplacingImageWithThumbField( _('Screenshot #4'), max_length=255, storage=demo_uploads_fs, upload_to=upload_screenshot_4, blank=True) screenshot_5 = ReplacingImageWithThumbField( _('Screenshot #5'), max_length=255, storage=demo_uploads_fs, upload_to=upload_screenshot_5, blank=True) video_url = VideoEmbedURLField( _("have a video of your demo in action? (optional)"), blank=True, null=True) demo_package = ReplacingZipFileField( _('select a ZIP file containing your demo'), max_length=255, max_upload_size=config_lazy('DEMO_MAX_ZIP_FILESIZE', 60 * 1024 * 1024), # overridden by constance storage=demo_uploads_fs, upload_to=demo_package_upload_to, blank=False) source_code_url = models.URLField( _("Is your source code also available somewhere else on the web (e.g., github)? Please share the link."), blank=True, null=True) license_name = models.CharField( _("Select the license that applies to your source code."), max_length=64, blank=False, choices=[(license['name'], license['title']) for license in DEMO_LICENSES.values()] ) creator = models.ForeignKey(settings.AUTH_USER_MODEL, blank=False, null=True) created = models.DateTimeField( _('date created'), auto_now_add=True, blank=False) modified = models.DateTimeField( _('date last modified'), auto_now=True, blank=False) def natural_key(self): return (self.slug,) def update(self, **kw): """ Shortcut for doing an UPDATE on this object. If _signal=False is in ``kw`` the post_save signal won't be sent. """ signal = kw.pop('_signal', True) cls = self.__class__ using = kw.pop('using', 'default') for k, v in kw.items(): setattr(self, k, v) if signal: # Detect any attribute changes during pre_save and add those to the # update kwargs. attrs = dict(self.__dict__) models.signals.pre_save.send(sender=cls, instance=self) for k, v in self.__dict__.items(): if attrs[k] != v: kw[k] = v setattr(self, k, v) cls.objects.using(using).filter(pk=self.pk).update(**kw) if signal: models.signals.post_save.send(sender=cls, instance=self, created=False) def censor(self, url=None): """Censor a demo, with optional link to explanation""" self.censored = True self.censored_url = url self.save() root = join(DEMO_UPLOADS_ROOT, get_root_for_submission(self)) if isdir(root): rmtree(root) def __unicode__(self): return 'Submission "%(title)s"' % dict(title=self.title) def get_absolute_url(self): return reverse('kuma.demos.views.detail', kwargs={'slug': self.slug}) def _make_unique_slug(self, **kwargs): """ Try to generate a unique 50-character slug. """ if self.slug: slug = self.slug[:50] else: slug = slugify(self.title)[:50] using = kwargs['using'] if 'using' in kwargs else 'default' existing = Submission.objects.using(using).filter(slug=slug) if (not existing) or (self.id and self.id in [s.id for s in existing]): return slug # If the first 50 characters aren't unique, we chop off the # last two and try sticking a two-digit number there. # # If for some reason we get to 100 demos which all have the # same first fifty characters in their title, this will # break. Hopefully that's unlikely enough that it won't be a # problem, but we can always add a check at the end of the # while loop or come up with some other method if we actually # run into it. base_slug = slug[:-2] i = 0 while Submission.objects.filter(slug=slug).exists() and i < 100: slug = "%s%02d" % (base_slug, i) i += 1 return slug def save(self, **kwargs): """Save the submission, updating slug and screenshot thumbnails""" self.slug = self._make_unique_slug(**kwargs) super(Submission, self).save(**kwargs) def delete(self, using=None): root = join(DEMO_UPLOADS_ROOT, get_root_for_submission(self)) if isdir(root): rmtree(root) super(Submission, self).delete(using) def clean(self): if self.demo_package: Submission.validate_demo_zipfile(self.demo_package) def next(self): """Find the next submission by created time, return None if not found.""" try: obj = self.get_next_by_created(hidden=False) return obj except Submission.DoesNotExist: return None def previous(self): """Find the previous submission by created time, return None if not found.""" try: obj = self.get_previous_by_created(hidden=False) return obj except Submission.DoesNotExist: return None def screenshot_url(self, index='1'): """Fetch the screenshot URL for a given index, swallowing errors""" try: return getattr(self, 'screenshot_%s' % index).url except: return '' def thumbnail_url(self, index='1'): """Fetch the screenshot thumbnail URL for a given index, swallowing errors""" try: return getattr(self, 'screenshot_%s' % index).thumbnail_url() except: return '' def get_flags(self): """ Assemble status flags, based on featured status and a set of special tags (eg. for Dev Derby). The flags are assembled in order of display priority, so the first flag on the list (if any) is the most important""" flags = [] # Iterate through known flags based on tag naming convention. Tag flags # are listed here in order of priority. tag_flags = ('firstplace', 'secondplace', 'thirdplace', 'finalist') or_queries = [] for tag_flag in tag_flags: term = 'system:challenge:%s:' % tag_flag or_queries.append(Q(**{'name__startswith': term})) for tag in self.taggit_tags.filter(reduce(operator.or_, or_queries)): split_tag_name = tag.name.split(':') if len(split_tag_name) > 2: # the first two items are ['system', 'challenge'] flags.append(split_tag_name[2]) # the third item is the tag name # Featured is an odd-man-out before we had tags if self.featured: flags.append('featured') return flags def is_derby_submission(self): return bool(self.taggit_tags.all_ns('challenge:')) def challenge_closed(self): challenge_tags = self.taggit_tags.all_ns('challenge:') if not challenge_tags or 'challenge:none' in map(str, challenge_tags): return False return challenge_utils.challenge_closed(challenge_tags) @classmethod def allows_listing_hidden_by(cls, user): return user.is_staff or user.is_superuser def allows_viewing_by(self, user): if not self.censored: return (user.is_staff or user.is_superuser or user.pk == self.creator.pk or not self.hidden) def allows_managing_by(self, user): return user.is_staff or user.is_superuser or user.pk == self.creator.pk @classmethod def get_valid_demo_zipfile_entries(cls, zf): """Filter a ZIP file's entries for only accepted entries""" # TODO: Move to zip file field? return [x for x in zf.infolist() if not (x.filename.startswith('/') or '/..' in x.filename) and not (basename(x.filename).startswith('.')) and x.file_size > 0] @classmethod def validate_demo_zipfile(cls, file): """Ensure a given file is a valid ZIP file without disallowed file entries and with an HTML index.""" # TODO: Move to zip file field? try: zf = zipfile.ZipFile(file) except: raise ValidationError(_('ZIP file contains no acceptable files')) if zf.testzip(): raise ValidationError(_('ZIP file corrupted')) valid_entries = Submission.get_valid_demo_zipfile_entries(zf) if len(valid_entries) == 0: raise ValidationError(_('ZIP file contains no acceptable files')) m_mime = magic.Magic(mime=True) index_found = False for zi in valid_entries: name = zi.filename # HACK: We're accepting {index,demo}.html as the root index and # normalizing on unpack if 'index.html' == name or 'demo.html' == name: index_found = True if zi.file_size > config.DEMO_MAX_FILESIZE_IN_ZIP: raise ValidationError( _('ZIP file contains a file that is too large: %(filename)s') % {"filename": name} ) file_data = zf.read(zi) # HACK: Sometimes we get "type; charset", even if charset wasn't asked for file_mime_type = m_mime.from_buffer(file_data).split(';')[0] extensions = config.DEMO_BLACKLIST_OVERRIDE_EXTENSIONS.split() override_file_extensions = ['.%s' % extension for extension in extensions] if (file_mime_type in DEMO_MIMETYPE_BLACKLIST and not name.endswith(tuple(override_file_extensions))): raise ValidationError( _('ZIP file contains an unacceptable file: %(filename)s') % {'filename': name}) if not index_found: raise ValidationError(_('HTML index not found in ZIP')) def process_demo_package(self): """Unpack the demo ZIP file into the appropriate directory, filtering out any invalid file entries and normalizing demo.html to index.html if present.""" # TODO: Move to zip file field? # Derive a directory name from the zip filename, clean up any existing # directory before unpacking. new_root_dir = self.demo_package.path.replace('.zip', '') if isdir(new_root_dir): rmtree(new_root_dir) # Load up the zip file and extract the valid entries zf = zipfile.ZipFile(self.demo_package.file) valid_entries = Submission.get_valid_demo_zipfile_entries(zf) for zi in valid_entries: if type(zi.filename) is unicode: zi_filename = zi.filename else: zi_filename = zi.filename.decode('utf-8', 'ignore') # HACK: Normalize demo.html to index.html if zi_filename == u'demo.html': zi_filename = u'index.html' # Relocate all files from detected root dir to a directory named # for the zip file in storage out_fn = join(new_root_dir, zi_filename) out_dir = dirname(out_fn) # Create parent directories where necessary. if not isdir(out_dir): makedirs(out_dir.encode('utf-8'), 0775) # Extract the file from the zip into the desired location. fout = open(out_fn.encode('utf-8'), 'wb') copyfileobj(zf.open(zi), fout)
sadanandb/pmt
refs/heads/master
src/pyasm/search/sobject_default_config.py
6
########################################################### # # Copyright (c) 2005, Southpaw Technology # All Rights Reserved # # PROPRIETARY INFORMATION. This software is proprietary to # Southpaw Technology, and is not to be reproduced, transmitted, # or disclosed in any way without written permission. # # # __all__ = ['SObjectDefaultConfig'] from pyasm.common import Base, Xml, Environment from pyasm.search import DbContainer, SearchType, SqlException, Sql class SObjectDefaultConfig(Base): '''An artificial config file is made if none are found''' def __init__(my, search_type, view, config_base=None, mode="columns"): my.search_type = search_type if view: my.view = view else: my.view = config_base if not my.view: my.view = "table" # bit of protection ... : have been known to show up in view names my.view = my.view.replace(":", '_') #mode = "basic" my.xml = Xml() if mode == 'columns': my.handle_columns_mode() else: my.handle_basic_mode() def get_columns(my, required_only=False): if my.search_type == 'sthpw/virtual': return [] search_type_obj = SearchType.get(my.search_type) table = search_type_obj.get_table() from pyasm.biz import Project db_resource = Project.get_db_resource_by_search_type(my.search_type) database_name = db_resource.get_database() db = DbContainer.get(db_resource) # table may not exist try: all_columns = db.get_columns(table) columns = [] if required_only: nullables = db.get_column_nullables(table) for column in all_columns: null_ok = nullables.get(column) if not null_ok: columns.append(column) # if there are no required columns if not columns: columns = all_columns else: columns = all_columns except SqlException: Environment.add_warning('missing table', 'Table [%s] does not exist in database [%s]' %(table, database_name)) return [] return columns def handle_basic_mode(my): doc = my.xml.create_doc("config") root = my.xml.get_root_node() db_columns = my.get_columns() if "code" in db_columns: columns = ["preview", "code"] elif "name" in db_columns: columns = ["preview", "name"] elif "id" in db_columns: columns = ["preview", "id"] table = my.xml.create_element("table") Xml.append_child(root, table) for column in ["preview", "code"]: element = my.xml.create_element("element") Xml.set_attribute(element, "name", column) Xml.append_child(table, element) # create the edit edit = my.xml.create_element("edit") Xml.append_child(root, edit) for column in ["preview", "code"]: element = my.xml.create_element("element") Xml.set_attribute(element, "name", column) Xml.append_child(edit, element) # create the manual publish view publish = my.xml.create_element("publish") Xml.append_child(root, publish) element = my.xml.create_element("element") Xml.set_attribute(element, "name", "image") Xml.append_child(publish, element) dis_element = my.xml.create_element("display") Xml.set_attribute(dis_element, "class", "ThumbInputWdg") act_element = my.xml.create_element("action") Xml.set_attribute(act_element, "class", "NullAction") Xml.append_child(element, dis_element) Xml.append_child(element, act_element) element = my.xml.create_element("element") Xml.set_attribute(element, "name", "publish_files") Xml.append_child(publish, element) dis_element = my.xml.create_element("display") Xml.set_attribute(dis_element, "class", "UploadWdg") # add options option = my.xml.create_text_element('names','publish_icon|publish_main') Xml.append_child(dis_element, option) option = my.xml.create_text_element('required','false|true') Xml.append_child(dis_element, option) act_element = my.xml.create_element("action") Xml.set_attribute(act_element, "class", "MultiUploadAction") # add options option = my.xml.create_text_element('names','publish_icon|publish_main') Xml.append_child(act_element, option) option = my.xml.create_text_element('types','icon_main|main') Xml.append_child(act_element, option) Xml.append_child(element, dis_element) Xml.append_child(element, act_element) value = my.xml.to_string() my.xml = Xml() my.xml.read_string(value) def handle_columns_mode(my): doc = my.xml.create_doc("config") root = my.xml.get_root_node() columns = my.get_columns() if len(columns) == 1 and columns[0] == "id": columns = my.get_columns(required_only=False) # create the table # search is a special view for SearchWdg and it should not be created if my.view not in ['search','publish']: table = my.xml.create_element(my.view) my.xml.append_child(root, table) for column in columns: if column in ["_id", "id", "oid", "s_status"]: continue element = my.xml.create_element("element") Xml.set_attribute(element, "name", column) my.xml.append_child(table, element) # add history, input and output for the load view (designed for app loading) if my.view == 'load': element = my.xml.create_element("element") Xml.set_attribute(element, "name", "checkin") my.xml.append_child(table, element) for column in ['input', 'output']: element = my.xml.create_element("element") Xml.set_attribute(element, "name", column) Xml.set_attribute(element, "edit", "false") display_element = my.xml.create_element("display") Xml.set_attribute(display_element, "class", "tactic.ui.cgapp.LoaderElementWdg") my.xml.append_child(element, display_element) stype, key = SearchType.break_up_key(my.search_type) op1 = my.xml.create_text_element("search_type", stype) op2 = my.xml.create_text_element("mode", column) my.xml.append_child(display_element, op1) my.xml.append_child(display_element, op2) my.xml.append_child(table, element) value = my.xml.to_string() my.xml = Xml() my.xml.read_string(value) def get_type(my, element_name): xpath = "config/%s/element[@name='%s']/@type" % (my.view,element_name) type = my.xml.get_value(xpath) if not type: xpath = "config/%s/element[@name='%s']/@type" % ("definition",element_name) type = my.xml.get_value(xpath) return type def get_xml(my): return my.xml
britcey/ansible
refs/heads/devel
contrib/inventory/vmware_inventory.py
28
#!/usr/bin/env python # Requirements # - pyvmomi >= 6.0.0.2016.4 # TODO: # * more jq examples # * optional folder heriarchy """ $ jq '._meta.hostvars[].config' data.json | head { "alternateguestname": "", "instanceuuid": "5035a5cd-b8e8-d717-e133-2d383eb0d675", "memoryhotaddenabled": false, "guestfullname": "Red Hat Enterprise Linux 7 (64-bit)", "changeversion": "2016-05-16T18:43:14.977925Z", "uuid": "4235fc97-5ddb-7a17-193b-9a3ac97dc7b4", "cpuhotremoveenabled": false, "vpmcenabled": false, "firmware": "bios", """ from __future__ import print_function import argparse import atexit import datetime import getpass import os import re import six import ssl import sys import uuid from collections import defaultdict from six.moves import configparser from time import time from jinja2 import Environment HAS_PYVMOMI = False try: from pyVmomi import vim from pyVim.connect import SmartConnect, Disconnect HAS_PYVMOMI = True except ImportError: pass try: import json except ImportError: import simplejson as json hasvcr = False try: import vcr hasvcr = True except ImportError: pass def regex_match(s, pattern): '''Custom filter for regex matching''' reg = re.compile(pattern) if reg.match(s): return True else: return False class VMwareMissingHostException(Exception): pass class VMWareInventory(object): __name__ = 'VMWareInventory' guest_props = False instances = [] debug = False load_dumpfile = None write_dumpfile = None maxlevel = 1 lowerkeys = True config = None cache_max_age = None cache_path_cache = None cache_path_index = None cache_dir = None server = None port = None username = None password = None validate_certs = True host_filters = [] skip_keys = [] groupby_patterns = [] if sys.version_info > (3, 0): safe_types = [int, bool, str, float, None] else: safe_types = [int, long, bool, str, float, None] iter_types = [dict, list] bad_types = ['Array', 'disabledMethod', 'declaredAlarmState'] vimTableMaxDepth = { "vim.HostSystem": 2, "vim.VirtualMachine": 2, } custom_fields = {} # use jinja environments to allow for custom filters env = Environment() env.filters['regex_match'] = regex_match # translation table for attributes to fetch for known vim types if not HAS_PYVMOMI: vimTable = {} else: vimTable = { vim.Datastore: ['_moId', 'name'], vim.ResourcePool: ['_moId', 'name'], vim.HostSystem: ['_moId', 'name'], } @staticmethod def _empty_inventory(): return {"_meta": {"hostvars": {}}} def __init__(self, load=True): self.inventory = VMWareInventory._empty_inventory() if load: # Read settings and parse CLI arguments self.parse_cli_args() self.read_settings() # Check the cache cache_valid = self.is_cache_valid() # Handle Cache if self.args.refresh_cache or not cache_valid: self.do_api_calls_update_cache() else: self.debugl('loading inventory from cache') self.inventory = self.get_inventory_from_cache() def debugl(self, text): if self.args.debug: try: text = str(text) except UnicodeEncodeError: text = text.encode('ascii', 'ignore') print('%s %s' % (datetime.datetime.now(), text)) def show(self): # Data to print self.debugl('dumping results') data_to_print = None if self.args.host: data_to_print = self.get_host_info(self.args.host) elif self.args.list: # Display list of instances for inventory data_to_print = self.inventory return json.dumps(data_to_print, indent=2) def is_cache_valid(self): ''' Determines if the cache files have expired, or if it is still valid ''' valid = False if os.path.isfile(self.cache_path_cache): mod_time = os.path.getmtime(self.cache_path_cache) current_time = time() if (mod_time + self.cache_max_age) > current_time: valid = True return valid def do_api_calls_update_cache(self): ''' Get instances and cache the data ''' self.inventory = self.instances_to_inventory(self.get_instances()) self.write_to_cache(self.inventory) def write_to_cache(self, data): ''' Dump inventory to json file ''' with open(self.cache_path_cache, 'wb') as f: f.write(json.dumps(data)) def get_inventory_from_cache(self): ''' Read in jsonified inventory ''' jdata = None with open(self.cache_path_cache, 'rb') as f: jdata = f.read() return json.loads(jdata) def read_settings(self): ''' Reads the settings from the vmware_inventory.ini file ''' scriptbasename = __file__ scriptbasename = os.path.basename(scriptbasename) scriptbasename = scriptbasename.replace('.py', '') defaults = {'vmware': { 'server': '', 'port': 443, 'username': '', 'password': '', 'validate_certs': True, 'ini_path': os.path.join(os.path.dirname(__file__), '%s.ini' % scriptbasename), 'cache_name': 'ansible-vmware', 'cache_path': '~/.ansible/tmp', 'cache_max_age': 3600, 'max_object_level': 1, 'skip_keys': 'declaredalarmstate,' 'disabledmethod,' 'dynamicproperty,' 'dynamictype,' 'environmentbrowser,' 'managedby,' 'parent,' 'childtype,' 'resourceconfig', 'alias_pattern': '{{ config.name + "_" + config.uuid }}', 'host_pattern': '{{ guest.ipaddress }}', 'host_filters': '{{ guest.gueststate == "running" }}', 'groupby_patterns': '{{ guest.guestid }},{{ "templates" if config.template else "guests"}}', 'lower_var_keys': True, 'custom_field_group_prefix': 'vmware_tag_', 'groupby_custom_field': False} } if six.PY3: config = configparser.ConfigParser() else: config = configparser.SafeConfigParser() # where is the config? vmware_ini_path = os.environ.get('VMWARE_INI_PATH', defaults['vmware']['ini_path']) vmware_ini_path = os.path.expanduser(os.path.expandvars(vmware_ini_path)) config.read(vmware_ini_path) # apply defaults for k, v in defaults['vmware'].items(): if not config.has_option('vmware', k): config.set('vmware', k, str(v)) # where is the cache? self.cache_dir = os.path.expanduser(config.get('vmware', 'cache_path')) if self.cache_dir and not os.path.exists(self.cache_dir): os.makedirs(self.cache_dir) # set the cache filename and max age cache_name = config.get('vmware', 'cache_name') self.cache_path_cache = self.cache_dir + "/%s.cache" % cache_name self.debugl('cache path is %s' % self.cache_path_cache) self.cache_max_age = int(config.getint('vmware', 'cache_max_age')) # mark the connection info self.server = os.environ.get('VMWARE_SERVER', config.get('vmware', 'server')) self.debugl('server is %s' % self.server) self.port = int(os.environ.get('VMWARE_PORT', config.get('vmware', 'port'))) self.username = os.environ.get('VMWARE_USERNAME', config.get('vmware', 'username')) self.debugl('username is %s' % self.username) self.password = os.environ.get('VMWARE_PASSWORD', config.get('vmware', 'password')) self.validate_certs = os.environ.get('VMWARE_VALIDATE_CERTS', config.get('vmware', 'validate_certs')) if self.validate_certs in ['no', 'false', 'False', False]: self.validate_certs = False self.debugl('cert validation is %s' % self.validate_certs) # behavior control self.maxlevel = int(config.get('vmware', 'max_object_level')) self.debugl('max object level is %s' % self.maxlevel) self.lowerkeys = config.get('vmware', 'lower_var_keys') if type(self.lowerkeys) != bool: if str(self.lowerkeys).lower() in ['yes', 'true', '1']: self.lowerkeys = True else: self.lowerkeys = False self.debugl('lower keys is %s' % self.lowerkeys) self.skip_keys = list(config.get('vmware', 'skip_keys').split(',')) self.debugl('skip keys is %s' % self.skip_keys) self.host_filters = list(config.get('vmware', 'host_filters').split(',')) self.debugl('host filters are %s' % self.host_filters) self.groupby_patterns = list(config.get('vmware', 'groupby_patterns').split(',')) self.debugl('groupby patterns are %s' % self.groupby_patterns) # Special feature to disable the brute force serialization of the # virtulmachine objects. The key name for these properties does not # matter because the values are just items for a larger list. if config.has_section('properties'): self.guest_props = [] for prop in config.items('properties'): self.guest_props.append(prop[1]) # save the config self.config = config def parse_cli_args(self): ''' Command line argument processing ''' parser = argparse.ArgumentParser(description='Produce an Ansible Inventory file based on PyVmomi') parser.add_argument('--debug', action='store_true', default=False, help='show debug info') parser.add_argument('--list', action='store_true', default=True, help='List instances (default: True)') parser.add_argument('--host', action='store', help='Get all the variables about a specific instance') parser.add_argument('--refresh-cache', action='store_true', default=False, help='Force refresh of cache by making API requests to VSphere (default: False - use cache files)') parser.add_argument('--max-instances', default=None, type=int, help='maximum number of instances to retrieve') self.args = parser.parse_args() def get_instances(self): ''' Get a list of vm instances with pyvmomi ''' kwargs = {'host': self.server, 'user': self.username, 'pwd': self.password, 'port': int(self.port)} if hasattr(ssl, 'SSLContext') and not self.validate_certs: context = ssl.SSLContext(ssl.PROTOCOL_SSLv23) context.verify_mode = ssl.CERT_NONE kwargs['sslContext'] = context return self._get_instances(kwargs) def _get_instances(self, inkwargs): ''' Make API calls ''' instances = [] si = SmartConnect(**inkwargs) self.debugl('retrieving all instances') if not si: print("Could not connect to the specified host using specified " "username and password") return -1 atexit.register(Disconnect, si) content = si.RetrieveContent() # Create a search container for virtualmachines self.debugl('creating containerview for virtualmachines') container = content.rootFolder viewType = [vim.VirtualMachine] recursive = True containerView = content.viewManager.CreateContainerView(container, viewType, recursive) children = containerView.view for child in children: # If requested, limit the total number of instances if self.args.max_instances: if len(instances) >= self.args.max_instances: break instances.append(child) self.debugl("%s total instances in container view" % len(instances)) if self.args.host: instances = [x for x in instances if x.name == self.args.host] instance_tuples = [] for instance in sorted(instances): if self.guest_props: ifacts = self.facts_from_proplist(instance) else: ifacts = self.facts_from_vobj(instance) instance_tuples.append((instance, ifacts)) self.debugl('facts collected for all instances') cfm = content.customFieldsManager if cfm is not None and cfm.field: for f in cfm.field: if f.managedObjectType == vim.VirtualMachine: self.custom_fields[f.key] = f.name self.debugl('%d custom fieds collected' % len(self.custom_fields)) return instance_tuples def instances_to_inventory(self, instances): ''' Convert a list of vm objects into a json compliant inventory ''' self.debugl('re-indexing instances based on ini settings') inventory = VMWareInventory._empty_inventory() inventory['all'] = {} inventory['all']['hosts'] = [] for idx, instance in enumerate(instances): # make a unique id for this object to avoid vmware's # numerous uuid's which aren't all unique. thisid = str(uuid.uuid4()) idata = instance[1] # Put it in the inventory inventory['all']['hosts'].append(thisid) inventory['_meta']['hostvars'][thisid] = idata.copy() inventory['_meta']['hostvars'][thisid]['ansible_uuid'] = thisid # Make a map of the uuid to the alias the user wants name_mapping = self.create_template_mapping( inventory, self.config.get('vmware', 'alias_pattern') ) # Make a map of the uuid to the ssh hostname the user wants host_mapping = self.create_template_mapping( inventory, self.config.get('vmware', 'host_pattern') ) # Reset the inventory keys for k, v in name_mapping.items(): if not host_mapping or not k in host_mapping: continue # set ansible_host (2.x) try: inventory['_meta']['hostvars'][k]['ansible_host'] = host_mapping[k] # 1.9.x backwards compliance inventory['_meta']['hostvars'][k]['ansible_ssh_host'] = host_mapping[k] except Exception: continue if k == v: continue # add new key inventory['all']['hosts'].append(v) inventory['_meta']['hostvars'][v] = inventory['_meta']['hostvars'][k] # cleanup old key inventory['all']['hosts'].remove(k) inventory['_meta']['hostvars'].pop(k, None) self.debugl('pre-filtered hosts:') for i in inventory['all']['hosts']: self.debugl(' * %s' % i) # Apply host filters for hf in self.host_filters: if not hf: continue self.debugl('filter: %s' % hf) filter_map = self.create_template_mapping(inventory, hf, dtype='boolean') for k, v in filter_map.items(): if not v: # delete this host inventory['all']['hosts'].remove(k) inventory['_meta']['hostvars'].pop(k, None) self.debugl('post-filter hosts:') for i in inventory['all']['hosts']: self.debugl(' * %s' % i) # Create groups for gbp in self.groupby_patterns: groupby_map = self.create_template_mapping(inventory, gbp) for k, v in groupby_map.items(): if v not in inventory: inventory[v] = {} inventory[v]['hosts'] = [] if k not in inventory[v]['hosts']: inventory[v]['hosts'].append(k) if self.config.get('vmware', 'groupby_custom_field'): for k, v in inventory['_meta']['hostvars'].items(): if 'customvalue' in v: for tv in v['customvalue']: if not isinstance(tv['value'], str) and not isinstance(tv['value'], unicode): continue newkey = None field_name = self.custom_fields[tv['key']] if tv['key'] in self.custom_fields else tv['key'] values = [] keylist = map(lambda x: x.strip(), tv['value'].split(',')) for kl in keylist: try: newkey = self.config.get('vmware', 'custom_field_group_prefix') + field_name + '_' + kl newkey = newkey.strip() except Exception as e: self.debugl(e) values.append(newkey) for tag in values: if not tag: continue if tag not in inventory: inventory[tag] = {} inventory[tag]['hosts'] = [] if k not in inventory[tag]['hosts']: inventory[tag]['hosts'].append(k) return inventory def create_template_mapping(self, inventory, pattern, dtype='string'): ''' Return a hash of uuid to templated string from pattern ''' mapping = {} for k, v in inventory['_meta']['hostvars'].items(): t = self.env.from_string(pattern) newkey = None try: newkey = t.render(v) newkey = newkey.strip() except Exception as e: self.debugl(e) if not newkey: continue elif dtype == 'integer': newkey = int(newkey) elif dtype == 'boolean': if newkey.lower() == 'false': newkey = False elif newkey.lower() == 'true': newkey = True elif dtype == 'string': pass mapping[k] = newkey return mapping def facts_from_proplist(self, vm): '''Get specific properties instead of serializing everything''' rdata = {} for prop in self.guest_props: self.debugl('getting %s property for %s' % (prop, vm.name)) key = prop if self.lowerkeys: key = key.lower() if '.' not in prop: # props without periods are direct attributes of the parent rdata[key] = getattr(vm, prop) else: # props with periods are subkeys of parent attributes parts = prop.split('.') total = len(parts) - 1 # pointer to the current object val = None # pointer to the current result key lastref = rdata for idx, x in enumerate(parts): # if the val wasn't set yet, get it from the parent if not val: try: val = getattr(vm, x) except AttributeError as e: self.debugl(e) else: # in a subkey, get the subprop from the previous attrib try: val = getattr(val, x) except AttributeError as e: self.debugl(e) # lowercase keys if requested if self.lowerkeys: x = x.lower() # change the pointer or set the final value if idx != total: if x not in lastref: lastref[x] = {} lastref = lastref[x] else: lastref[x] = val return rdata def facts_from_vobj(self, vobj, level=0): ''' Traverse a VM object and return a json compliant data structure ''' # pyvmomi objects are not yet serializable, but may be one day ... # https://github.com/vmware/pyvmomi/issues/21 # WARNING: # Accessing an object attribute will trigger a SOAP call to the remote. # Increasing the attributes collected or the depth of recursion greatly # increases runtime duration and potentially memory+network utilization. if level == 0: try: self.debugl("get facts for %s" % vobj.name) except Exception as e: self.debugl(e) rdata = {} methods = dir(vobj) methods = [str(x) for x in methods if not x.startswith('_')] methods = [x for x in methods if x not in self.bad_types] methods = [x for x in methods if not x.lower() in self.skip_keys] methods = sorted(methods) for method in methods: # Attempt to get the method, skip on fail try: methodToCall = getattr(vobj, method) except Exception as e: continue # Skip callable methods if callable(methodToCall): continue if self.lowerkeys: method = method.lower() rdata[method] = self._process_object_types( methodToCall, thisvm=vobj, inkey=method, ) return rdata def _process_object_types(self, vobj, thisvm=None, inkey=None, level=0): ''' Serialize an object ''' rdata = {} if type(vobj).__name__ in self.vimTableMaxDepth and level >= self.vimTableMaxDepth[type(vobj).__name__]: return rdata if vobj is None: rdata = None elif type(vobj) in self.vimTable: rdata = {} for key in self.vimTable[type(vobj)]: try: rdata[key] = getattr(vobj, key) except Exception as e: self.debugl(e) elif issubclass(type(vobj), str) or isinstance(vobj, str): if vobj.isalnum(): rdata = vobj else: rdata = vobj.decode('ascii', 'ignore') elif issubclass(type(vobj), bool) or isinstance(vobj, bool): rdata = vobj elif issubclass(type(vobj), int) or isinstance(vobj, int): rdata = vobj elif issubclass(type(vobj), float) or isinstance(vobj, float): rdata = vobj elif issubclass(type(vobj), long) or isinstance(vobj, long): rdata = vobj elif issubclass(type(vobj), list) or issubclass(type(vobj), tuple): rdata = [] try: vobj = sorted(vobj) except Exception: pass for idv, vii in enumerate(vobj): if level + 1 <= self.maxlevel: vid = self._process_object_types( vii, thisvm=thisvm, inkey=inkey + '[' + str(idv) + ']', level=(level + 1) ) if vid: rdata.append(vid) elif issubclass(type(vobj), dict): pass elif issubclass(type(vobj), object): methods = dir(vobj) methods = [str(x) for x in methods if not x.startswith('_')] methods = [x for x in methods if x not in self.bad_types] methods = [x for x in methods if not inkey + '.' + x.lower() in self.skip_keys] methods = sorted(methods) for method in methods: # Attempt to get the method, skip on fail try: methodToCall = getattr(vobj, method) except Exception as e: continue if callable(methodToCall): continue if self.lowerkeys: method = method.lower() if level + 1 <= self.maxlevel: try: rdata[method] = self._process_object_types( methodToCall, thisvm=thisvm, inkey=inkey + '.' + method, level=(level + 1) ) except vim.fault.NoPermission: self.debugl("Skipping method %s (NoPermission)" % method) else: pass return rdata def get_host_info(self, host): ''' Return hostvars for a single host ''' if host in self.inventory['_meta']['hostvars']: return self.inventory['_meta']['hostvars'][host] elif self.args.host and self.inventory['_meta']['hostvars']: match = None for k, v in self.inventory['_meta']['hostvars']: if self.inventory['_meta']['hostvars'][k]['name'] == self.args.host: match = k break if match: return self.inventory['_meta']['hostvars'][match] else: raise VMwareMissingHostException('%s not found' % host) else: raise VMwareMissingHostException('%s not found' % host) if __name__ == "__main__": # Run the script print(VMWareInventory().show())
cernops/nova
refs/heads/master
nova/virt/virtapi.py
23
# Copyright 2012 IBM Corp. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import contextlib class VirtAPI(object): @contextlib.contextmanager def wait_for_instance_event(self, instance, event_names, deadline=300, error_callback=None): raise NotImplementedError()
haidarvm/hadits
refs/heads/master
assets/post.py
1
from urllib.request import Request, urlopen from urllib import parse,error url = 'http://192.168.12.30/post.php' value = {"test" : 'testing' , "data" : 'haidar123' } parse_data = parse.urlencode(value) try: ropen = urlopen(url, parse_data.encode('utf-8')) print(ropen.read()) except error.URLError as e: print("URL Error:",e.read() , url)
HaebinShin/tensorflow
refs/heads/master
tensorflow/python/kernel_tests/sparse_ops_test.py
1
# Copyright 2015 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Tests for Python ops defined in sparse_ops.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes from tensorflow.python.framework import ops from tensorflow.python.framework import test_util from tensorflow.python.ops import array_ops from tensorflow.python.ops import sparse_ops from tensorflow.python.platform import googletest # TODO(zongheng): it'd be great to factor out this function and various random # SparseTensor gen funcs. def _sparsify(x, thresh=0.5, index_dtype=np.int64): x[x < thresh] = 0 non_zero = np.where(x) x_indices = np.vstack(non_zero).astype(index_dtype).T x_values = x[non_zero] x_shape = x.shape return ops.SparseTensor( indices=x_indices, values=x_values, shape=x_shape), len(x_values) class SparseToIndicatorTest(test_util.TensorFlowTestCase): def _SparseTensor_5x6(self, dtype): ind = np.array([ [0, 0], [1, 0], [1, 3], [1, 4], [3, 2], [3, 3]]) val = np.array([0, 10, 13, 14, 32, 33]) shape = np.array([5, 6]) return ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(val, dtype), constant_op.constant(shape, dtypes.int64)) def _SparseTensor_2x3x4(self, dtype): # Includes two entries with the form [1, 1, x] : 150. ind = np.array([ [0, 0, 1], [0, 1, 0], [0, 1, 2], [1, 0, 3], [1, 1, 0], [1, 1, 1], [1, 1, 2], [1, 2, 2]]) val = np.array([1, 10, 12, 103, 150, 149, 150, 122]) shape = np.array([2, 3, 4]) return ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(val, dtype), constant_op.constant(shape, dtypes.int64)) def testInt32(self): with self.test_session(use_gpu=False): sp_input = self._SparseTensor_5x6(dtypes.int32) output = sparse_ops.sparse_to_indicator(sp_input, 50).eval() expected_output = np.zeros((5, 50), dtype=np.bool) expected_trues = ((0, 0), (1, 10), (1, 13), (1, 14), (3, 32), (3, 33)) for expected_true in expected_trues: expected_output[expected_true] = True self.assertAllEqual(output, expected_output) def testInt64(self): with self.test_session(use_gpu=False): sp_input = self._SparseTensor_5x6(dtypes.int64) output = sparse_ops.sparse_to_indicator(sp_input, 50).eval() expected_output = np.zeros((5, 50), dtype=np.bool) expected_trues = [(0, 0), (1, 10), (1, 13), (1, 14), (3, 32), (3, 33)] for expected_true in expected_trues: expected_output[expected_true] = True self.assertAllEqual(output, expected_output) def testHigherRank(self): with self.test_session(use_gpu=False): sp_input = self._SparseTensor_2x3x4(dtypes.int64) output = sparse_ops.sparse_to_indicator(sp_input, 200).eval() expected_output = np.zeros((2, 3, 200), dtype=np.bool) expected_trues = [(0, 0, 1), (0, 1, 10), (0, 1, 12), (1, 0, 103), (1, 1, 149), (1, 1, 150), (1, 2, 122)] for expected_true in expected_trues: expected_output[expected_true] = True self.assertAllEqual(output, expected_output) class SparseMergeTest(test_util.TensorFlowTestCase): def _SparseTensor_3x50(self, indices_dtype, values_dtype): ind = np.array([ [0, 0], [1, 0], [1, 1], [1, 2], [2, 0], [2, 1]]) # NB: these are not sorted indices = np.array([0, 13, 10, 14, 32, 33]) values = np.array([-3, 4, 1, 1, 5, 9]) shape = np.array([3, 3]) indices = ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(indices, indices_dtype), constant_op.constant(shape, dtypes.int64)) values = ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(values, values_dtype), constant_op.constant(shape, dtypes.int64)) return indices, values def testInt32AndFloat32(self): vocab_size = 50 with self.test_session(use_gpu=False) as sess: indices, values = self._SparseTensor_3x50(dtypes.int32, dtypes.float32) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) output = sess.run(sp_output) self.assertAllEqual( output.indices, [[0, 0], [1, 10], [1, 13], [1, 14], [2, 32], [2, 33]]) self.assertAllEqual( output.values, [-3, 1, 4, 1, 5, 9]) self.assertAllEqual( output.shape, [3, vocab_size]) def testInt64AndFloat32(self): vocab_size = 50 with self.test_session(use_gpu=False) as sess: indices, values = self._SparseTensor_3x50(dtypes.int64, dtypes.float32) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) output = sess.run(sp_output) self.assertAllEqual( output.indices, [[0, 0], [1, 10], [1, 13], [1, 14], [2, 32], [2, 33]]) self.assertAllEqual( output.values, [-3, 1, 4, 1, 5, 9]) self.assertAllEqual( output.shape, [3, vocab_size]) def testInt64AndFloat64(self): vocab_size = 50 with self.test_session(use_gpu=False) as sess: indices, values = self._SparseTensor_3x50(dtypes.int64, dtypes.float64) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) output = sess.run(sp_output) self.assertAllEqual( output.indices, [[0, 0], [1, 10], [1, 13], [1, 14], [2, 32], [2, 33]]) self.assertAllEqual( output.values, [-3, 1, 4, 1, 5, 9]) self.assertAllEqual( output.shape, [3, vocab_size]) class SparseRetainTest(test_util.TensorFlowTestCase): def _SparseTensor_5x6(self): ind = np.array([ [0, 0], [1, 0], [1, 3], [1, 4], [3, 2], [3, 3]]) val = np.array([0, 10, 13, 14, 32, 33]) shape = np.array([5, 6]) return ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(val, dtypes.int32), constant_op.constant(shape, dtypes.int64)) def testBasic(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_5x6() to_retain = np.array([1, 0, 0, 1, 1, 0], dtype=np.bool) sp_output = sparse_ops.sparse_retain(sp_input, to_retain) output = sess.run(sp_output) self.assertAllEqual(output.indices, [[0, 0], [1, 4], [3, 2]]) self.assertAllEqual(output.values, [0, 14, 32]) self.assertAllEqual(output.shape, [5, 6]) def testRetainNone(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_5x6() to_retain = np.zeros((6,), dtype=np.bool) sp_output = sparse_ops.sparse_retain(sp_input, to_retain) output = sess.run(sp_output) self.assertAllEqual(output.indices, np.array([]).reshape((0, 2))) self.assertAllEqual(output.values, []) self.assertAllEqual(output.shape, [5, 6]) def testMismatchedRetainShape(self): with self.test_session(use_gpu=False): sp_input = self._SparseTensor_5x6() to_retain = np.array([1, 0, 0, 1, 0], dtype=np.bool) with self.assertRaises(ValueError): sparse_ops.sparse_retain(sp_input, to_retain) class SparseResetShapeTest(test_util.TensorFlowTestCase): _IND_2_5_6 = np.array([[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]], dtype=np.int64) _VAL_2_5_6 = np.array([0, 10, 13, 14, 32, 33], dtype=np.int32) _SHP_2_5_6 = np.array([2, 5, 6], dtype=np.int64) def _SparseTensor_2x5x6(self): return ops.SparseTensor( constant_op.constant(self._IND_2_5_6, dtypes.int64), constant_op.constant(self._VAL_2_5_6, dtypes.int32), constant_op.constant(self._SHP_2_5_6, dtypes.int64)) def _SparseTensorValue_2x5x6(self): return ops.SparseTensorValue(self._IND_2_5_6, self._VAL_2_5_6, self._SHP_2_5_6) def testBasic(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_2x5x6() new_shape = np.array([3, 6, 7], dtype=np.int64) sp_output = sparse_ops.sparse_reset_shape(sp_input, new_shape) output = sess.run(sp_output) self.assertAllEqual(output.indices, [[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]]) self.assertAllEqual(output.values, [0, 10, 13, 14, 32, 33]) self.assertAllEqual(output.shape, [3, 6, 7]) def testInputUnavaibleInGraphConstructionOk(self): with self.test_session(use_gpu=False) as sess: sp_input = array_ops.sparse_placeholder(dtype=dtypes.int32) new_shape = np.array([3, 6, 7], dtype=np.int64) sp_output = sparse_ops.sparse_reset_shape(sp_input, new_shape) output = sess.run(sp_output, feed_dict={sp_input: self._SparseTensorValue_2x5x6()}) self.assertAllEqual(output.indices, [[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]]) self.assertAllEqual(output.values, [0, 10, 13, 14, 32, 33]) self.assertAllEqual(output.shape, [3, 6, 7]) def testTightBoundingBox(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_2x5x6() sp_output = sparse_ops.sparse_reset_shape(sp_input) output = sess.run(sp_output) self.assertAllEqual(output.indices, [[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]]) self.assertAllEqual(output.values, [0, 10, 13, 14, 32, 33]) self.assertAllEqual(output.shape, [2, 4, 5]) def testInvalidRank(self): with self.test_session(use_gpu=False): sp_input = self._SparseTensor_2x5x6() new_shape = np.array([3, 7], dtype=np.int64) with self.assertRaises(ValueError): sparse_ops.sparse_reset_shape(sp_input, new_shape) def testInvalidRankNewShapeUnavaibleInGraphConstruction(self): with self.test_session(use_gpu=False) as sess: new_shape = array_ops.placeholder(dtype=dtypes.int64) sp_input = self._SparseTensor_2x5x6() out = sparse_ops.sparse_reset_shape(sp_input, new_shape) with self.assertRaisesOpError("x == y did not hold element-wise"): sess.run(out, feed_dict={new_shape: np.array([3, 7], dtype=np.int64)}) def testInvalidDimensionSize(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_2x5x6() new_shape = np.array([3, 7, 5], dtype=np.int64) out = sparse_ops.sparse_reset_shape(sp_input, new_shape) with self.assertRaisesOpError("x <= y did not hold element-wise"): sess.run(out) def testInvalidDimensionSizeInputUnavailableInGraphConstruction(self): sp_input = array_ops.sparse_placeholder(dtype=dtypes.int32) with self.test_session(use_gpu=False) as sess: new_shape = np.array([3, 7, 5], dtype=np.int64) out = sparse_ops.sparse_reset_shape(sp_input, new_shape) with self.assertRaisesOpError("x <= y did not hold element-wise"): sess.run(out, feed_dict={sp_input: self._SparseTensorValue_2x5x6()}) class SparseFillEmptyRowsTest(test_util.TensorFlowTestCase): def _SparseTensor_5x6(self): ind = np.array([ [0, 0], [1, 0], [1, 3], [1, 4], [3, 2], [3, 3]]) val = np.array([0, 10, 13, 14, 32, 33]) shape = np.array([5, 6]) return ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(val, dtypes.int32), constant_op.constant(shape, dtypes.int64)) def _SparseTensor_String5x6(self): ind = np.array([ [0, 0], [1, 0], [1, 3], [1, 4], [3, 2], [3, 3]]) val = np.array(["a", "b", "c", "d", "e", "f"]) shape = np.array([5, 6]) return ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(val, dtypes.string), constant_op.constant(shape, dtypes.int64)) def _SparseTensor_2x6(self): ind = np.array([[0, 0], [1, 0], [1, 3], [1, 4]]) val = np.array([0, 10, 13, 14]) shape = np.array([2, 6]) return ops.SparseTensor( constant_op.constant(ind, dtypes.int64), constant_op.constant(val, dtypes.int32), constant_op.constant(shape, dtypes.int64)) def testFillNumber(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_5x6() sp_output, empty_row_indicator = ( sparse_ops.sparse_fill_empty_rows(sp_input, -1)) output, empty_row_indicator_out = sess.run( [sp_output, empty_row_indicator]) self.assertAllEqual( output.indices, [[0, 0], [1, 0], [1, 3], [1, 4], [2, 0], [3, 2], [3, 3], [4, 0]]) self.assertAllEqual(output.values, [0, 10, 13, 14, -1, 32, 33, -1]) self.assertAllEqual(output.shape, [5, 6]) self.assertAllEqual(empty_row_indicator_out, np.array([0, 0, 1, 0, 1]).astype(np.bool)) def testFillString(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_String5x6() sp_output, empty_row_indicator = ( sparse_ops.sparse_fill_empty_rows(sp_input, "")) output, empty_row_indicator_out = sess.run( [sp_output, empty_row_indicator]) self.assertAllEqual( output.indices, [[0, 0], [1, 0], [1, 3], [1, 4], [2, 0], [3, 2], [3, 3], [4, 0]]) self.assertAllEqual(output.values, [b"a", b"b", b"c", b"d", b"", b"e", b"f", b""]) self.assertAllEqual(output.shape, [5, 6]) self.assertAllEqual(empty_row_indicator_out, np.array([0, 0, 1, 0, 1]).astype(np.bool)) def testNoEmptyRows(self): with self.test_session(use_gpu=False) as sess: sp_input = self._SparseTensor_2x6() sp_output, empty_row_indicator = ( sparse_ops.sparse_fill_empty_rows(sp_input, -1)) output, empty_row_indicator_out = sess.run( [sp_output, empty_row_indicator]) self.assertAllEqual(output.indices, [[0, 0], [1, 0], [1, 3], [1, 4]]) self.assertAllEqual(output.values, [0, 10, 13, 14]) self.assertAllEqual(output.shape, [2, 6]) self.assertAllEqual(empty_row_indicator_out, np.zeros(2).astype(np.bool)) class SparseReduceSumTest(test_util.TensorFlowTestCase): # [[1, ?, 1] # [?, 1, ?]] # where ? is implictly-zero. ind = np.array([[0, 0], [0, 2], [1, 1]]).astype(np.int64) vals = np.array([1, 1, 1]).astype(np.int32) shape = np.array([2, 3]).astype(np.int64) def _compare(self, sp_t, reduction_axes, ndims, keep_dims): densified = sparse_ops.sparse_tensor_to_dense(sp_t).eval() np_ans = densified if reduction_axes is None: np_ans = np.sum(np_ans, keepdims=keep_dims) else: if not isinstance(reduction_axes, list): # Single scalar. reduction_axes = [reduction_axes] reduction_axes = np.array(reduction_axes).astype(np.int32) # Handles negative axes. reduction_axes = (reduction_axes + ndims) % ndims # Loop below depends on sorted. reduction_axes.sort() for ra in reduction_axes.ravel()[::-1]: np_ans = np.sum(np_ans, axis=ra, keepdims=keep_dims) with self.test_session(): tf_ans = sparse_ops.sparse_reduce_sum(sp_t, reduction_axes, keep_dims) out = tf_ans.eval() self.assertAllClose(np_ans, out) def _compare_all(self, sp_t, reduction_axes, ndims): self._compare(sp_t, reduction_axes, ndims, False) self._compare(sp_t, reduction_axes, ndims, True) def testSimpleAndRandomInputs(self): sp_t = ops.SparseTensor(self.ind, self.vals, self.shape) with self.test_session(use_gpu=False): self._compare_all(sp_t, None, ndims=2) self._compare_all(sp_t, 0, ndims=2) self._compare_all(sp_t, [1], ndims=2) self._compare_all(sp_t, [0, 1], ndims=2) self._compare_all(sp_t, [1, 0], ndims=2) self._compare_all(sp_t, [-1], ndims=2) self._compare_all(sp_t, [1, -2], ndims=2) np.random.seed(1618) test_dims = [(1618, 1, 11, 7, 1), (1,), (1, 1, 1)] with self.test_session(use_gpu=False): for dims in test_dims: sp_t, unused_nnz = _sparsify(np.random.randn(*dims)) # reduce all using None self._compare_all(sp_t, None, ndims=len(dims)) # reduce random axes from 1D to N-D for d in range(1, len(dims) + 1): axes = np.random.choice(len(dims), size=d, replace=False).tolist() self._compare_all(sp_t, axes, ndims=len(dims)) def testInvalidAxes(self): sp_t = ops.SparseTensor(self.ind, self.vals, self.shape) with self.test_session(use_gpu=False): with self.assertRaisesOpError("Invalid reduction dimension -3"): sparse_ops.sparse_reduce_sum(sp_t, -3).eval() with self.assertRaisesOpError("Invalid reduction dimension 2"): sparse_ops.sparse_reduce_sum(sp_t, 2).eval() def testGradient(self): np.random.seed(8161) test_dims = [(11, 1, 5, 7, 1), (2, 2)] with self.test_session(use_gpu=False): for dims in test_dims: sp_t, nnz = _sparsify(np.random.randn(*dims)) # reduce random axes from 1D to N-D for d in range(1, len(dims) + 1): axes = np.random.choice(len(dims), size=d, replace=False).tolist() reduced = sparse_ops.sparse_reduce_sum(sp_t, axes) err = tf.test.compute_gradient_error(sp_t.values, (nnz,), reduced, reduced.eval().shape) self.assertLess(err, 1e-3) # Tests for negative axes. reduced = sparse_ops.sparse_reduce_sum(sp_t, -1) err = tf.test.compute_gradient_error(sp_t.values, (nnz,), reduced, reduced.eval().shape) self.assertLess(err, 1e-3) class SparseMathOpsTest(test_util.TensorFlowTestCase): def _check(self, result_tensor, result_np, input_sp_t): self.assertTrue(isinstance(result_tensor, ops.SparseTensor)) self.assertTrue(isinstance(input_sp_t, ops.SparseTensor)) self.assertAllEqual(input_sp_t.indices.eval(), result_tensor.indices.eval()) self.assertAllEqual(input_sp_t.shape.eval(), result_tensor.shape.eval()) res_densified = sparse_ops.sparse_to_dense(result_tensor.indices, result_tensor.shape, result_tensor.values).eval() self.assertAllEqual(result_np, res_densified) def testCwiseDivAndMul(self): np.random.seed(1618) sp_shapes = [(10, 10, 10), (5, 5), (1618,), (3, 3, 7)] dense_shapes = [(10, 10, 1), (5, 5), (1,), (1, 7)] with self.test_session(use_gpu=False): for dtype in [np.float32, np.float64, np.int32, np.int64]: for sp_shape, dense_shape in zip(sp_shapes, dense_shapes): sp_vals_np = np.random.rand(*sp_shape).astype(dtype) + 1 dense_vals_np = np.random.rand(*dense_shape).astype(dtype) + 1 sp_t, unused_nnz = _sparsify(sp_vals_np, thresh=1.5) sp_t_densified = sparse_ops.sparse_tensor_to_dense(sp_t).eval() dense_t = tf.constant(dense_vals_np) self._check(sp_t / dense_t, sp_t_densified / dense_vals_np, sp_t) # Check commutative. self._check(sp_t * dense_t, sp_t_densified * dense_vals_np, sp_t) self._check(dense_t * sp_t, sp_t_densified * dense_vals_np, sp_t) if dtype in [np.int32, np.int64]: res = sp_t / dense_t # should invoke "__truediv__" self.assertEqual(res.values.eval().dtype, np.float64) def testCwiseAdd(self): with self.test_session(use_gpu=False): # Identity(2) + AllOnes(2,2). Should be equal to 2 * Identity(2). indices = [[0, 0], [1, 1]] vals = [1, 1] shape = (2, 2) sp_t = tf.SparseTensor(indices, vals, shape) dense_t = tf.ones(shape, dtype=dtypes.int32) self._check(sparse_ops.sparse_dense_cwise_add(sp_t, dense_t), np.identity(2) * 2, sp_t) # Variant of above, but broadcasts the dense side. dense_t = tf.ones([1], dtype=dtypes.int32) self._check(sparse_ops.sparse_dense_cwise_add(sp_t, dense_t), np.identity(2) * 2, sp_t) def testGradients(self): np.random.seed(1618) sp_shapes = [(10, 10, 10), (5, 5), (1618,), (3, 3, 7)] dense_shapes = [(10, 10, 1), (5, 5), (1,), (1, 7)] with self.test_session(use_gpu=False): for dtype in [np.float32, np.float64]: for sp_shape, dense_shape in zip(sp_shapes, dense_shapes): sp_vals_np = np.random.rand(*sp_shape).astype(dtype) + 1 dense_vals_np = np.random.rand(*dense_shape).astype(dtype) + 1 sp_t, nnz = _sparsify(sp_vals_np, thresh=1.5) dense_t = tf.constant(dense_vals_np) cmul = sp_t * dense_t err = tf.test.compute_gradient_error([sp_t.values, dense_t], [(nnz,), dense_shape], cmul.values, (nnz,)) self.assertLess(err, 1e-4) cdiv = sp_t / dense_t err = tf.test.compute_gradient_error(sp_t.values, (nnz,), cdiv.values, (nnz,)) self.assertLess(err, 1e-4) err = tf.test.compute_gradient_error(dense_t, dense_shape, cdiv.values, (nnz,), x_init_value=dense_vals_np) self.assertLess(err, 2e-4) class SparseSoftmaxTest(test_util.TensorFlowTestCase): def testEquivalentToDensified(self): np.random.seed(1618) n, m = np.random.choice(20, size=2) for dtype in [np.float32, np.float64]: sp_vals_np = np.random.rand(n, m).astype(dtype) batched_sp_t, unused_nnz1 = _sparsify( sp_vals_np.reshape((1, n, m)), thresh=0.) # No masking. with self.test_session(use_gpu=False): densified = tf.constant(sp_vals_np) sp_result = sparse_ops.sparse_softmax( batched_sp_t).eval().values.reshape((n, m)) dense_result = tf.nn.softmax(densified) self.assertAllClose(dense_result.eval(), sp_result) def testHigherRanks(self): # For the first shape: # First batch: # [? e.] # [1. ? ] # Second batch: # [e ? ] # [e e ] # # The softmax results should be: # [? 1.] [1 ?] # [1. ? ] and [.5 .5] # where ? means implicitly zero. # # The second shape: same input data, but with a higher-rank shape. shapes = [[2, 2, 2], [2, 1, 2, 2]] for shape in shapes: values = np.asarray( [0., np.e, 1., 0., np.e, 0., np.e, np.e]).reshape(shape) sp_t, unused_nnz = _sparsify(values, thresh=1e-2) expected_values = [1., 1., 1., .5, .5] with self.test_session(use_gpu=False): result = sparse_ops.sparse_softmax(sp_t).eval() self.assertAllEqual(expected_values, result.values) self.assertAllEqual(sp_t.indices.eval(), result.indices) self.assertAllEqual(shape, result.shape) def testGradient(self): x_shape = [2, 5, 10] with self.test_session(use_gpu=False): for dtype in [np.float32, np.float64]: x_np = np.random.randn(*x_shape).astype(dtype) x_tf, nnz = _sparsify(x_np) y_tf = tf.sparse_softmax(x_tf) err = tf.test.compute_gradient_error(x_tf.values, (nnz,), y_tf.values, (nnz,)) self.assertLess(err, 1e-4) class SparseMinimumMaximumTest(test_util.TensorFlowTestCase): def _assertSparseTensorValueEqual(self, a, b): self.assertAllEqual(a.indices, b.indices) self.assertAllEqual(a.values, b.values) self.assertAllEqual(a.shape, b.shape) def testBasic(self): with self.test_session(use_gpu=False): # 1-D, values at index 0. sp_zero = ops.SparseTensor([[0]], [0], [7]) sp_one = ops.SparseTensor([[0]], [1], [7]) max_tf = tf.sparse_maximum(sp_zero, sp_one).eval() min_tf = tf.sparse_minimum(sp_zero, sp_one).eval() self._assertSparseTensorValueEqual(sp_one.eval(), max_tf) self._assertSparseTensorValueEqual(sp_zero.eval(), min_tf) # Values at different indices. sp_zero = ops.SparseTensor([[0]], [0], [7]) sp_zero_2 = ops.SparseTensor([[1]], [0], [7]) expected = ops.SparseTensor([[0], [1]], [0, 0], [7]) max_tf = tf.sparse_maximum(sp_zero, sp_zero_2).eval() min_tf = tf.sparse_minimum(sp_zero, sp_zero_2).eval() self._assertSparseTensorValueEqual(expected.eval(), max_tf) self._assertSparseTensorValueEqual(expected.eval(), min_tf) def testRandom(self): np.random.seed(1618) shapes = [(13,), (6, 8), (1, 7, 1)] for shape in shapes: for dtype in [np.int32, np.int64, np.float16, np.float32, np.float64]: a_np = np.random.randn(*shape).astype(dtype) b_np = np.random.randn(*shape).astype(dtype) sp_a, unused_a_nnz = _sparsify(a_np, thresh=-.5) sp_b, unused_b_nnz = _sparsify(b_np, thresh=-.5) with self.test_session(use_gpu=False): maximum_tf = tf.sparse_maximum(sp_a, sp_b) maximum_tf_densified = tf.sparse_tensor_to_dense(maximum_tf).eval() minimum_tf = tf.sparse_minimum(sp_a, sp_b) minimum_tf_densified = tf.sparse_tensor_to_dense(minimum_tf).eval() a_densified = tf.sparse_tensor_to_dense(sp_a).eval() b_densified = tf.sparse_tensor_to_dense(sp_b).eval() self.assertAllEqual( np.maximum(a_densified, b_densified), maximum_tf_densified) self.assertAllEqual( np.minimum(a_densified, b_densified), minimum_tf_densified) def testMismatchedShapes(self): with self.test_session(use_gpu=False): sp_zero = ops.SparseTensor([[0, 0]], [0], [1, 1]) sp_one = ops.SparseTensor([[0]], [1], [2]) with self.assertRaisesOpError("Operands do not have the same ranks"): tf.sparse_maximum(sp_zero, sp_one).eval() sp_zero = ops.SparseTensor([[0]], [0], [1]) sp_one = ops.SparseTensor([[0]], [1], [2]) with self.assertRaisesOpError("Operands' shapes do not match"): tf.sparse_maximum(sp_zero, sp_one).eval() if __name__ == "__main__": googletest.main()
ville-k/tensorflow
refs/heads/master
tensorflow/contrib/keras/python/keras/models_test.py
7
# Copyright 2016 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Tests for training routines.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import tempfile import numpy as np from tensorflow.contrib.keras.python import keras from tensorflow.python.platform import test try: import h5py # pylint:disable=g-import-not-at-top except ImportError: h5py = None class TestModelSaving(test.TestCase): def test_sequential_model_saving(self): if h5py is None: return # Skip test if models cannot be saved. with self.test_session(): model = keras.models.Sequential() model.add(keras.layers.Dense(2, input_shape=(3,))) model.add(keras.layers.RepeatVector(3)) model.add(keras.layers.TimeDistributed(keras.layers.Dense(3))) model.compile(loss=keras.losses.MSE, optimizer=keras.optimizers.RMSprop(lr=0.0001), metrics=[keras.metrics.categorical_accuracy], sample_weight_mode='temporal') x = np.random.random((1, 3)) y = np.random.random((1, 3, 3)) model.train_on_batch(x, y) out = model.predict(x) _, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) new_model = keras.models.load_model(fname) os.remove(fname) out2 = new_model.predict(x) self.assertAllClose(out, out2, atol=1e-05) # test that new updates are the same with both models x = np.random.random((1, 3)) y = np.random.random((1, 3, 3)) model.train_on_batch(x, y) new_model.train_on_batch(x, y) out = model.predict(x) out2 = new_model.predict(x) self.assertAllClose(out, out2, atol=1e-05) def test_sequential_model_saving_2(self): if h5py is None: return # Skip test if models cannot be saved. with self.test_session(): # test with custom optimizer, loss class CustomOp(keras.optimizers.RMSprop): pass def custom_loss(y_true, y_pred): return keras.losses.mse(y_true, y_pred) model = keras.models.Sequential() model.add(keras.layers.Dense(2, input_shape=(3,))) model.add(keras.layers.Dense(3)) model.compile(loss=custom_loss, optimizer=CustomOp(), metrics=['acc']) x = np.random.random((1, 3)) y = np.random.random((1, 3)) model.train_on_batch(x, y) out = model.predict(x) _, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model( fname, custom_objects={'CustomOp': CustomOp, 'custom_loss': custom_loss}) os.remove(fname) out2 = model.predict(x) self.assertAllClose(out, out2, atol=1e-05) def test_functional_model_saving(self): if h5py is None: return # Skip test if models cannot be saved. with self.test_session(): inputs = keras.layers.Input(shape=(3,)) x = keras.layers.Dense(2)(inputs) output = keras.layers.Dense(3)(x) model = keras.models.Model(inputs, output) model.compile(loss=keras.losses.MSE, optimizer=keras.optimizers.RMSprop(lr=0.0001), metrics=[keras.metrics.categorical_accuracy]) x = np.random.random((1, 3)) y = np.random.random((1, 3)) model.train_on_batch(x, y) out = model.predict(x) _, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) os.remove(fname) out2 = model.predict(x) self.assertAllClose(out, out2, atol=1e-05) def test_saving_without_compilation(self): if h5py is None: return # Skip test if models cannot be saved. with self.test_session(): model = keras.models.Sequential() model.add(keras.layers.Dense(2, input_shape=(3,))) model.add(keras.layers.Dense(3)) model.compile(loss='mse', optimizer='sgd', metrics=['acc']) _, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) os.remove(fname) def test_saving_right_after_compilation(self): if h5py is None: return # Skip test if models cannot be saved. with self.test_session(): model = keras.models.Sequential() model.add(keras.layers.Dense(2, input_shape=(3,))) model.add(keras.layers.Dense(3)) model.compile(loss='mse', optimizer='sgd', metrics=['acc']) model.model._make_train_function() _, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) os.remove(fname) class TestSequential(test.TestCase): """Most Sequential model API tests are covered in `training_test.py`. """ def test_sequential_pop(self): num_hidden = 5 input_dim = 3 batch_size = 5 num_classes = 2 with self.test_session(): model = keras.models.Sequential() model.add(keras.layers.Dense(num_hidden, input_dim=input_dim)) model.add(keras.layers.Dense(num_classes)) model.compile(loss='mse', optimizer='sgd') x = np.random.random((batch_size, input_dim)) y = np.random.random((batch_size, num_classes)) model.fit(x, y, epochs=1) model.pop() self.assertEqual(len(model.layers), 1) self.assertEqual(model.output_shape, (None, num_hidden)) model.compile(loss='mse', optimizer='sgd') y = np.random.random((batch_size, num_hidden)) model.fit(x, y, epochs=1) if __name__ == '__main__': test.main()
woggle/mesos-old
refs/heads/trunk
frameworks/hadoop-0.20.2/src/contrib/hod/hodlib/Common/descGenerator.py
182
#Licensed to the Apache Software Foundation (ASF) under one #or more contributor license agreements. See the NOTICE file #distributed with this work for additional information #regarding copyright ownership. The ASF licenses this file #to you under the Apache License, Version 2.0 (the #"License"); you may not use this file except in compliance #with the License. You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 #Unless required by applicable law or agreed to in writing, software #distributed under the License is distributed on an "AS IS" BASIS, #WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #See the License for the specific language governing permissions and #limitations under the License. """manage hod configuration""" # -*- python -*- import sys, csv, os from optparse import Option, OptionParser from xml.dom import minidom from sets import Set from select import select, poll, POLLIN from hodlib.Common.desc import * class DescGenerator: """Contains the conversion to descriptors and other method calls to config""" def __init__(self, hodConfig): """parse all the descriptors""" self.hodConfig = hodConfig def initializeDesc(self): self.hodConfig['nodepooldesc'] = self.createNodePoolDesc() self.hodConfig['servicedesc'] = self.createServiceDescDict() return self.hodConfig def getServices(self): """get all the services from the config""" sdd = {} for keys in self.hodConfig: if keys.startswith('gridservice-'): str = keys.split('-') dict = self.hodConfig[keys] if 'server-params' in dict: dict['attrs'] = dict['server-params'] if 'final-server-params' in dict: dict['final-attrs'] = dict['final-server-params'] dict['id'] = str[1] desc = ServiceDesc(dict) sdd[desc.getName()] = desc return sdd def createNodePoolDesc(self): """ create a node pool descriptor and store it in hodconfig""" desc = NodePoolDesc(self.hodConfig['resource_manager']) return desc def createServiceDescDict(self): """create a service descriptor for all the services and store it in the hodconfig""" sdd = self.getServices() return sdd
culturagovbr/sistema-nacional-cultura
refs/heads/master
planotrabalho/migrations/0011_auto_20181206_1127.py
1
# Generated by Django 2.0.8 on 2018-12-06 16:34 from django.db import migrations, models from planotrabalho.models import Componente, Conselheiro from adesao.models import SistemaCultura, Municipio import django.db.models.deletion def migra_conselheiros(apps, schema_editor): conselheiros = apps.get_model('planotrabalho', 'Conselheiro') for conselheiro in conselheiros.objects.all(): municipio = Municipio.objects.get(usuario__plano_trabalho__conselho_cultural__id=conselheiro.conselho_aux.id) if municipio.cidade: sistemas = SistemaCultura.sistema.filter(ente_federado__nome=municipio.cidade.nome_municipio) codigo_ibge = str(municipio.cidade.codigo_ibge) else: sistemas = SistemaCultura.sistema.filter(ente_federado__nome=municipio.estado.nome_uf) codigo_ibge = str(municipio.estado.codigo_ibge) if sistemas.count() > 1: for sistema in sistemas: if codigo_ibge in str(sistema.ente_federado.cod_ibge): sistema_conselho = sistema break elif sistemas.count() == 1: sistema_conselho = sistemas[0] else: continue conselheiro.conselho_id = sistema_conselho.conselho.id conselheiro.save() class Migration(migrations.Migration): dependencies = [ ('planotrabalho', '0010_auto_20181203_1847'), ] operations = [ migrations.RenameField( model_name='conselheiro', old_name='conselho', new_name='conselho_aux', ), migrations.AddField( model_name='conselheiro', name='conselho', field=models.ForeignKey(to='planotrabalho.Componente', on_delete=django.db.models.deletion.CASCADE, null=True), ), migrations.RunPython(migra_conselheiros), migrations.RemoveField( model_name='conselheiro', name='conselho_aux', ), ]
jcpowermac/ansible
refs/heads/devel
test/runner/lib/executor.py
5
"""Execute Ansible tests.""" from __future__ import absolute_import, print_function import json import os import collections import datetime import re import tempfile import time import textwrap import functools import pipes import hashlib import lib.pytar import lib.thread from lib.core_ci import ( AnsibleCoreCI, SshKey, ) from lib.manage_ci import ( ManageWindowsCI, ManageNetworkCI, ) from lib.cloud import ( cloud_filter, cloud_init, get_cloud_environment, get_cloud_platforms, ) from lib.util import ( ApplicationWarning, ApplicationError, SubprocessError, display, run_command, intercept_command, remove_tree, make_dirs, is_shippable, is_binary_file, find_pip, find_executable, raw_command, get_coverage_path, ) from lib.ansible_util import ( ansible_environment, ) from lib.target import ( IntegrationTarget, walk_external_targets, walk_internal_targets, walk_posix_integration_targets, walk_network_integration_targets, walk_windows_integration_targets, walk_units_targets, ) from lib.changes import ( ShippableChanges, LocalChanges, ) from lib.git import ( Git, ) from lib.classification import ( categorize_changes, ) from lib.config import ( TestConfig, EnvironmentConfig, IntegrationConfig, NetworkIntegrationConfig, PosixIntegrationConfig, ShellConfig, UnitsConfig, WindowsIntegrationConfig, ) SUPPORTED_PYTHON_VERSIONS = ( '2.6', '2.7', '3.5', '3.6', '3.7', ) def check_startup(): """Checks to perform at startup before running commands.""" check_legacy_modules() def check_legacy_modules(): """Detect conflicts with legacy core/extras module directories to avoid problems later.""" for directory in 'core', 'extras': path = 'lib/ansible/modules/%s' % directory for root, _, file_names in os.walk(path): if file_names: # the directory shouldn't exist, but if it does, it must contain no files raise ApplicationError('Files prohibited in "%s". ' 'These are most likely legacy modules from version 2.2 or earlier.' % root) def create_shell_command(command): """ :type command: list[str] :rtype: list[str] """ optional_vars = ( 'TERM', ) cmd = ['/usr/bin/env'] cmd += ['%s=%s' % (var, os.environ[var]) for var in optional_vars if var in os.environ] cmd += command return cmd def install_command_requirements(args): """ :type args: EnvironmentConfig """ generate_egg_info(args) if not args.requirements: return packages = [] if isinstance(args, TestConfig): if args.coverage: packages.append('coverage') if args.junit: packages.append('junit-xml') pip = find_pip(version=args.python_version) commands = [generate_pip_install(pip, args.command, packages=packages)] if isinstance(args, IntegrationConfig): for cloud_platform in get_cloud_platforms(args): commands.append(generate_pip_install(pip, '%s.cloud.%s' % (args.command, cloud_platform))) commands = [cmd for cmd in commands if cmd] # only look for changes when more than one requirements file is needed detect_pip_changes = len(commands) > 1 # first pass to install requirements, changes expected unless environment is already set up changes = run_pip_commands(args, pip, commands, detect_pip_changes) if not changes: return # no changes means we can stop early # second pass to check for conflicts in requirements, changes are not expected here changes = run_pip_commands(args, pip, commands, detect_pip_changes) if not changes: return # no changes means no conflicts raise ApplicationError('Conflicts detected in requirements. The following commands reported changes during verification:\n%s' % '\n'.join((' '.join(pipes.quote(c) for c in cmd) for cmd in changes))) def run_pip_commands(args, pip, commands, detect_pip_changes=False): """ :type args: EnvironmentConfig :type pip: str :type commands: list[list[str]] :type detect_pip_changes: bool :rtype: list[list[str]] """ changes = [] after_list = pip_list(args, pip) if detect_pip_changes else None for cmd in commands: if not cmd: continue before_list = after_list try: run_command(args, cmd) except SubprocessError as ex: if ex.status != 2: raise # If pip is too old it won't understand the arguments we passed in, so we'll need to upgrade it. # Installing "coverage" on ubuntu 16.04 fails with the error: # AttributeError: 'Requirement' object has no attribute 'project_name' # See: https://bugs.launchpad.net/ubuntu/xenial/+source/python-pip/+bug/1626258 # Upgrading pip works around the issue. run_command(args, [pip, 'install', '--upgrade', 'pip']) run_command(args, cmd) after_list = pip_list(args, pip) if detect_pip_changes else None if before_list != after_list: changes.append(cmd) return changes def pip_list(args, pip): """ :type args: EnvironmentConfig :type pip: str :rtype: str """ stdout, _ = run_command(args, [pip, 'list'], capture=True) return stdout def generate_egg_info(args): """ :type args: EnvironmentConfig """ if os.path.isdir('lib/ansible.egg-info'): return run_command(args, ['python%s' % args.python_version, 'setup.py', 'egg_info'], capture=args.verbosity < 3) def generate_pip_install(pip, command, packages=None): """ :type pip: str :type command: str :type packages: list[str] | None :rtype: list[str] | None """ constraints = 'test/runner/requirements/constraints.txt' requirements = 'test/runner/requirements/%s.txt' % command options = [] if os.path.exists(requirements) and os.path.getsize(requirements): options += ['-r', requirements] if packages: options += packages if not options: return None return [pip, 'install', '--disable-pip-version-check', '-c', constraints] + options def command_shell(args): """ :type args: ShellConfig """ if args.delegate: raise Delegate() install_command_requirements(args) cmd = create_shell_command(['bash', '-i']) run_command(args, cmd) def command_posix_integration(args): """ :type args: PosixIntegrationConfig """ all_targets = tuple(walk_posix_integration_targets(include_hidden=True)) internal_targets = command_integration_filter(args, all_targets) command_integration_filtered(args, internal_targets, all_targets) def command_network_integration(args): """ :type args: NetworkIntegrationConfig """ default_filename = 'test/integration/inventory.networking' if args.inventory: filename = os.path.join('test/integration', args.inventory) else: filename = default_filename if not args.explain and not args.platform and not os.path.exists(filename): if args.inventory: filename = os.path.abspath(filename) raise ApplicationError( 'Inventory not found: %s\n' 'Use --inventory to specify the inventory path.\n' 'Use --platform to provision resources and generate an inventory file.\n' 'See also inventory template: %s.template' % (filename, default_filename) ) all_targets = tuple(walk_network_integration_targets(include_hidden=True)) internal_targets = command_integration_filter(args, all_targets, init_callback=network_init) instances = [] # type: list [lib.thread.WrappedThread] if args.platform: get_coverage_path(args) # initialize before starting threads configs = dict((config['platform_version'], config) for config in args.metadata.instance_config) for platform_version in args.platform: platform, version = platform_version.split('/', 1) config = configs.get(platform_version) if not config: continue instance = lib.thread.WrappedThread(functools.partial(network_run, args, platform, version, config)) instance.daemon = True instance.start() instances.append(instance) while any(instance.is_alive() for instance in instances): time.sleep(1) remotes = [instance.wait_for_result() for instance in instances] inventory = network_inventory(remotes) display.info('>>> Inventory: %s\n%s' % (filename, inventory.strip()), verbosity=3) if not args.explain: with open(filename, 'w') as inventory_fd: inventory_fd.write(inventory) success = False try: command_integration_filtered(args, internal_targets, all_targets) success = True finally: if args.remote_terminate == 'always' or (args.remote_terminate == 'success' and success): for instance in instances: instance.result.stop() def network_init(args, internal_targets): """ :type args: NetworkIntegrationConfig :type internal_targets: tuple[IntegrationTarget] """ if not args.platform: return if args.metadata.instance_config is not None: return platform_targets = set(a for t in internal_targets for a in t.aliases if a.startswith('network/')) instances = [] # type: list [lib.thread.WrappedThread] # generate an ssh key (if needed) up front once, instead of for each instance SshKey(args) for platform_version in args.platform: platform, version = platform_version.split('/', 1) platform_target = 'network/%s/' % platform if platform_target not in platform_targets: display.warning('Skipping "%s" because selected tests do not target the "%s" platform.' % ( platform_version, platform)) continue instance = lib.thread.WrappedThread(functools.partial(network_start, args, platform, version)) instance.daemon = True instance.start() instances.append(instance) while any(instance.is_alive() for instance in instances): time.sleep(1) args.metadata.instance_config = [instance.wait_for_result() for instance in instances] def network_start(args, platform, version): """ :type args: NetworkIntegrationConfig :type platform: str :type version: str :rtype: AnsibleCoreCI """ core_ci = AnsibleCoreCI(args, platform, version, stage=args.remote_stage, provider=args.remote_provider) core_ci.start() return core_ci.save() def network_run(args, platform, version, config): """ :type args: NetworkIntegrationConfig :type platform: str :type version: str :type config: dict[str, str] :rtype: AnsibleCoreCI """ core_ci = AnsibleCoreCI(args, platform, version, stage=args.remote_stage, provider=args.remote_provider, load=False) core_ci.load(config) core_ci.wait() manage = ManageNetworkCI(core_ci) manage.wait() return core_ci def network_inventory(remotes): """ :type remotes: list[AnsibleCoreCI] :rtype: str """ groups = dict([(remote.platform, []) for remote in remotes]) net = [] for remote in remotes: options = dict( ansible_host=remote.connection.hostname, ansible_user=remote.connection.username, ansible_ssh_private_key_file=os.path.abspath(remote.ssh_key.key), ansible_network_os=remote.platform, ansible_connection='local' ) groups[remote.platform].append( '%s %s' % ( remote.name.replace('.', '-'), ' '.join('%s="%s"' % (k, options[k]) for k in sorted(options)), ) ) net.append(remote.platform) groups['net:children'] = net template = '' for group in groups: hosts = '\n'.join(groups[group]) template += textwrap.dedent(""" [%s] %s """) % (group, hosts) inventory = template return inventory def command_windows_integration(args): """ :type args: WindowsIntegrationConfig """ filename = 'test/integration/inventory.winrm' if not args.explain and not args.windows and not os.path.isfile(filename): raise ApplicationError('Use the --windows option or provide an inventory file (see %s.template).' % filename) all_targets = tuple(walk_windows_integration_targets(include_hidden=True)) internal_targets = command_integration_filter(args, all_targets, init_callback=windows_init) instances = [] # type: list [lib.thread.WrappedThread] if args.windows: get_coverage_path(args) # initialize before starting threads configs = dict((config['platform_version'], config) for config in args.metadata.instance_config) for version in args.windows: config = configs['windows/%s' % version] instance = lib.thread.WrappedThread(functools.partial(windows_run, args, version, config)) instance.daemon = True instance.start() instances.append(instance) while any(instance.is_alive() for instance in instances): time.sleep(1) remotes = [instance.wait_for_result() for instance in instances] inventory = windows_inventory(remotes) display.info('>>> Inventory: %s\n%s' % (filename, inventory.strip()), verbosity=3) if not args.explain: with open(filename, 'w') as inventory_fd: inventory_fd.write(inventory) success = False try: command_integration_filtered(args, internal_targets, all_targets) success = True finally: if args.remote_terminate == 'always' or (args.remote_terminate == 'success' and success): for instance in instances: instance.result.stop() def windows_init(args, internal_targets): # pylint: disable=locally-disabled, unused-argument """ :type args: WindowsIntegrationConfig :type internal_targets: tuple[IntegrationTarget] """ if not args.windows: return if args.metadata.instance_config is not None: return instances = [] # type: list [lib.thread.WrappedThread] for version in args.windows: instance = lib.thread.WrappedThread(functools.partial(windows_start, args, version)) instance.daemon = True instance.start() instances.append(instance) while any(instance.is_alive() for instance in instances): time.sleep(1) args.metadata.instance_config = [instance.wait_for_result() for instance in instances] def windows_start(args, version): """ :type args: WindowsIntegrationConfig :type version: str :rtype: AnsibleCoreCI """ core_ci = AnsibleCoreCI(args, 'windows', version, stage=args.remote_stage, provider=args.remote_provider) core_ci.start() return core_ci.save() def windows_run(args, version, config): """ :type args: WindowsIntegrationConfig :type version: str :type config: dict[str, str] :rtype: AnsibleCoreCI """ core_ci = AnsibleCoreCI(args, 'windows', version, stage=args.remote_stage, provider=args.remote_provider, load=False) core_ci.load(config) core_ci.wait() manage = ManageWindowsCI(core_ci) manage.wait() return core_ci def windows_inventory(remotes): """ :type remotes: list[AnsibleCoreCI] :rtype: str """ hosts = [] for remote in remotes: options = dict( ansible_host=remote.connection.hostname, ansible_user=remote.connection.username, ansible_password=remote.connection.password, ansible_port=remote.connection.port, ) hosts.append( '%s %s' % ( remote.name.replace('/', '_'), ' '.join('%s="%s"' % (k, options[k]) for k in sorted(options)), ) ) template = """ [windows] %s [windows:vars] ansible_connection=winrm ansible_winrm_server_cert_validation=ignore # support winrm connection tests (temporary solution, does not support testing enable/disable of pipelining) [winrm:children] windows # support winrm binary module tests (temporary solution) [testhost_binary_modules:children] windows """ template = textwrap.dedent(template) inventory = template % ('\n'.join(hosts)) return inventory def command_integration_filter(args, targets, init_callback=None): """ :type args: IntegrationConfig :type targets: collections.Iterable[IntegrationTarget] :type init_callback: (IntegrationConfig, tuple[IntegrationTarget]) -> None :rtype: tuple[IntegrationTarget] """ targets = tuple(target for target in targets if 'hidden/' not in target.aliases) changes = get_changes_filter(args) require = (args.require or []) + changes exclude = (args.exclude or []) internal_targets = walk_internal_targets(targets, args.include, exclude, require) environment_exclude = get_integration_filter(args, internal_targets) environment_exclude += cloud_filter(args, internal_targets) if environment_exclude: exclude += environment_exclude internal_targets = walk_internal_targets(targets, args.include, exclude, require) if not internal_targets: raise AllTargetsSkipped() if args.start_at and not any(t.name == args.start_at for t in internal_targets): raise ApplicationError('Start at target matches nothing: %s' % args.start_at) if init_callback: init_callback(args, internal_targets) cloud_init(args, internal_targets) if args.delegate: raise Delegate(require=changes, exclude=exclude) install_command_requirements(args) return internal_targets def command_integration_filtered(args, targets, all_targets): """ :type args: IntegrationConfig :type targets: tuple[IntegrationTarget] :type all_targets: tuple[IntegrationTarget] """ found = False passed = [] failed = [] targets_iter = iter(targets) all_targets_dict = dict((target.name, target) for target in all_targets) setup_errors = [] setup_targets_executed = set() for target in all_targets: for setup_target in target.setup_once + target.setup_always: if setup_target not in all_targets_dict: setup_errors.append('Target "%s" contains invalid setup target: %s' % (target.name, setup_target)) if setup_errors: raise ApplicationError('Found %d invalid setup aliases:\n%s' % (len(setup_errors), '\n'.join(setup_errors))) test_dir = os.path.expanduser('~/ansible_testing') if not args.explain and any('needs/ssh/' in target.aliases for target in targets): max_tries = 20 display.info('SSH service required for tests. Checking to make sure we can connect.') for i in range(1, max_tries + 1): try: run_command(args, ['ssh', '-o', 'BatchMode=yes', 'localhost', 'id'], capture=True) display.info('SSH service responded.') break except SubprocessError: if i == max_tries: raise seconds = 3 display.warning('SSH service not responding. Waiting %d second(s) before checking again.' % seconds) time.sleep(seconds) start_at_task = args.start_at_task results = {} for target in targets_iter: if args.start_at and not found: found = target.name == args.start_at if not found: continue if args.list_targets: print(target.name) continue tries = 2 if args.retry_on_error else 1 verbosity = args.verbosity cloud_environment = get_cloud_environment(args, target) original_environment = EnvironmentDescription(args) display.info('>>> Environment Description\n%s' % original_environment, verbosity=3) try: while tries: tries -= 1 try: run_setup_targets(args, test_dir, target.setup_once, all_targets_dict, setup_targets_executed, False) start_time = time.time() run_setup_targets(args, test_dir, target.setup_always, all_targets_dict, setup_targets_executed, True) if not args.explain: # create a fresh test directory for each test target remove_tree(test_dir) make_dirs(test_dir) if target.script_path: command_integration_script(args, target) else: command_integration_role(args, target, start_at_task) start_at_task = None end_time = time.time() results[target.name] = dict( name=target.name, type=target.type, aliases=target.aliases, modules=target.modules, run_time_seconds=int(end_time - start_time), setup_once=target.setup_once, setup_always=target.setup_always, coverage=args.coverage, coverage_label=args.coverage_label, python_version=args.python_version, ) break except SubprocessError: if cloud_environment: cloud_environment.on_failure(target, tries) if not original_environment.validate(target.name, throw=False): raise if not tries: raise display.warning('Retrying test target "%s" with maximum verbosity.' % target.name) display.verbosity = args.verbosity = 6 start_time = time.time() original_environment.validate(target.name, throw=True) end_time = time.time() results[target.name]['validation_seconds'] = int(end_time - start_time) passed.append(target) except Exception as ex: failed.append(target) if args.continue_on_error: display.error(ex) continue display.notice('To resume at this test target, use the option: --start-at %s' % target.name) next_target = next(targets_iter, None) if next_target: display.notice('To resume after this test target, use the option: --start-at %s' % next_target.name) raise finally: display.verbosity = args.verbosity = verbosity if not args.explain: results_path = 'test/results/data/%s-%s.json' % (args.command, re.sub(r'[^0-9]', '-', str(datetime.datetime.utcnow().replace(microsecond=0)))) data = dict( targets=results, ) with open(results_path, 'w') as results_fd: results_fd.write(json.dumps(data, sort_keys=True, indent=4)) if failed: raise ApplicationError('The %d integration test(s) listed below (out of %d) failed. See error output above for details:\n%s' % ( len(failed), len(passed) + len(failed), '\n'.join(target.name for target in failed))) def run_setup_targets(args, test_dir, target_names, targets_dict, targets_executed, always): """ :param args: IntegrationConfig :param test_dir: str :param target_names: list[str] :param targets_dict: dict[str, IntegrationTarget] :param targets_executed: set[str] :param always: bool """ for target_name in target_names: if not always and target_name in targets_executed: continue target = targets_dict[target_name] if not args.explain: # create a fresh test directory for each test target remove_tree(test_dir) make_dirs(test_dir) if target.script_path: command_integration_script(args, target) else: command_integration_role(args, target, None) targets_executed.add(target_name) def integration_environment(args, target, cmd): """ :type args: IntegrationConfig :type target: IntegrationTarget :type cmd: list[str] :rtype: dict[str, str] """ env = ansible_environment(args) integration = dict( JUNIT_OUTPUT_DIR=os.path.abspath('test/results/junit'), ANSIBLE_CALLBACK_WHITELIST='junit', ANSIBLE_TEST_CI=args.metadata.ci_provider, ) if args.debug_strategy: env.update(dict(ANSIBLE_STRATEGY='debug')) if 'non_local/' in target.aliases: if args.coverage: display.warning('Skipping coverage reporting for non-local test: %s' % target.name) env.update(dict(ANSIBLE_TEST_REMOTE_INTERPRETER='')) env.update(integration) cloud_environment = get_cloud_environment(args, target) if cloud_environment: cloud_environment.configure_environment(env, cmd) return env def command_integration_script(args, target): """ :type args: IntegrationConfig :type target: IntegrationTarget """ display.info('Running %s integration test script' % target.name) cmd = ['./%s' % os.path.basename(target.script_path)] if args.verbosity: cmd.append('-' + ('v' * args.verbosity)) env = integration_environment(args, target, cmd) cwd = target.path intercept_command(args, cmd, target_name=target.name, env=env, cwd=cwd) def command_integration_role(args, target, start_at_task): """ :type args: IntegrationConfig :type target: IntegrationTarget :type start_at_task: str | None """ display.info('Running %s integration test role' % target.name) vars_file = 'integration_config.yml' if isinstance(args, WindowsIntegrationConfig): inventory = 'inventory.winrm' hosts = 'windows' gather_facts = False elif isinstance(args, NetworkIntegrationConfig): inventory = args.inventory or 'inventory.networking' hosts = target.name[:target.name.find('_')] gather_facts = False else: inventory = 'inventory' hosts = 'testhost' gather_facts = True cloud_environment = get_cloud_environment(args, target) if cloud_environment: hosts = cloud_environment.inventory_hosts or hosts playbook = ''' - hosts: %s gather_facts: %s roles: - { role: %s } ''' % (hosts, gather_facts, target.name) with tempfile.NamedTemporaryFile(dir='test/integration', prefix='%s-' % target.name, suffix='.yml') as pb_fd: pb_fd.write(playbook.encode('utf-8')) pb_fd.flush() filename = os.path.basename(pb_fd.name) display.info('>>> Playbook: %s\n%s' % (filename, playbook.strip()), verbosity=3) cmd = ['ansible-playbook', filename, '-i', inventory, '-e', '@%s' % vars_file] if start_at_task: cmd += ['--start-at-task', start_at_task] if args.tags: cmd += ['--tags', args.tags] if args.skip_tags: cmd += ['--skip-tags', args.skip_tags] if args.diff: cmd += ['--diff'] if args.verbosity: cmd.append('-' + ('v' * args.verbosity)) env = integration_environment(args, target, cmd) cwd = 'test/integration' env['ANSIBLE_ROLES_PATH'] = os.path.abspath('test/integration/targets') intercept_command(args, cmd, target_name=target.name, env=env, cwd=cwd) def command_units(args): """ :type args: UnitsConfig """ changes = get_changes_filter(args) require = (args.require or []) + changes include, exclude = walk_external_targets(walk_units_targets(), args.include, args.exclude, require) if not include: raise AllTargetsSkipped() if args.delegate: raise Delegate(require=changes) install_command_requirements(args) version_commands = [] for version in SUPPORTED_PYTHON_VERSIONS: # run all versions unless version given, in which case run only that version if args.python and version != args.python_version: continue env = ansible_environment(args) cmd = [ 'pytest', '--boxed', '-r', 'a', '--color', 'yes' if args.color else 'no', '--junit-xml', 'test/results/junit/python%s-units.xml' % version, ] if args.collect_only: cmd.append('--collect-only') if args.verbosity: cmd.append('-' + ('v' * args.verbosity)) if exclude: cmd += ['--ignore=%s' % target.path for target in exclude] cmd += [target.path for target in include] version_commands.append((version, cmd, env)) for version, command, env in version_commands: display.info('Unit test with Python %s' % version) try: intercept_command(args, command, target_name='units', env=env, python_version=version) except SubprocessError as ex: # pytest exits with status code 5 when all tests are skipped, which isn't an error for our use case if ex.status != 5: raise def get_changes_filter(args): """ :type args: TestConfig :rtype: list[str] """ paths = detect_changes(args) if paths is None: return [] # change detection not enabled, do not filter targets if not paths: raise NoChangesDetected() commands = categorize_changes(args, paths, args.command) targets = commands.get(args.command) if targets is None: raise NoTestsForChanges() if targets == ['all']: return [] # changes require testing all targets, do not filter targets return targets def detect_changes(args): """ :type args: TestConfig :rtype: list[str] | None """ if args.changed and is_shippable(): display.info('Shippable detected, collecting parameters from environment.') paths = detect_changes_shippable(args) elif args.changed_from or args.changed_path: paths = args.changed_path or [] if args.changed_from: with open(args.changed_from, 'r') as changes_fd: paths += changes_fd.read().splitlines() elif args.changed: paths = detect_changes_local(args) else: return None # change detection not enabled if paths is None: return None # act as though change detection not enabled, do not filter targets display.info('Detected changes in %d file(s).' % len(paths)) for path in paths: display.info(path, verbosity=1) return paths def detect_changes_shippable(args): """Initialize change detection on Shippable. :type args: TestConfig :rtype: list[str] | None """ git = Git(args) result = ShippableChanges(args, git) if result.is_pr: job_type = 'pull request' elif result.is_tag: job_type = 'tag' else: job_type = 'merge commit' display.info('Processing %s for branch %s commit %s' % (job_type, result.branch, result.commit)) if not args.metadata.changes: args.metadata.populate_changes(result.diff) return result.paths def detect_changes_local(args): """ :type args: TestConfig :rtype: list[str] """ git = Git(args) result = LocalChanges(args, git) display.info('Detected branch %s forked from %s at commit %s' % ( result.current_branch, result.fork_branch, result.fork_point)) if result.untracked and not args.untracked: display.warning('Ignored %s untracked file(s). Use --untracked to include them.' % len(result.untracked)) if result.committed and not args.committed: display.warning('Ignored %s committed change(s). Omit --ignore-committed to include them.' % len(result.committed)) if result.staged and not args.staged: display.warning('Ignored %s staged change(s). Omit --ignore-staged to include them.' % len(result.staged)) if result.unstaged and not args.unstaged: display.warning('Ignored %s unstaged change(s). Omit --ignore-unstaged to include them.' % len(result.unstaged)) names = set() if args.tracked: names |= set(result.tracked) if args.untracked: names |= set(result.untracked) if args.committed: names |= set(result.committed) if args.staged: names |= set(result.staged) if args.unstaged: names |= set(result.unstaged) if not args.metadata.changes: args.metadata.populate_changes(result.diff) for path in result.untracked: if is_binary_file(path): args.metadata.changes[path] = ((0, 0),) continue with open(path, 'r') as source_fd: line_count = len(source_fd.read().splitlines()) args.metadata.changes[path] = ((1, line_count),) return sorted(names) def get_integration_filter(args, targets): """ :type args: IntegrationConfig :type targets: tuple[IntegrationTarget] :rtype: list[str] """ if args.tox: # tox has the same exclusions as the local environment return get_integration_local_filter(args, targets) if args.docker: return get_integration_docker_filter(args, targets) if args.remote: return get_integration_remote_filter(args, targets) return get_integration_local_filter(args, targets) def get_integration_local_filter(args, targets): """ :type args: IntegrationConfig :type targets: tuple[IntegrationTarget] :rtype: list[str] """ exclude = [] if os.getuid() != 0: skip = 'needs/root/' skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which require running as root: %s' % (skip.rstrip('/'), ', '.join(skipped))) # consider explicit testing of destructive as though --allow-destructive was given include_destructive = any(target.startswith('destructive/') for target in args.include) if not args.allow_destructive and not include_destructive: skip = 'destructive/' skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which require --allow-destructive to run locally: %s' % (skip.rstrip('/'), ', '.join(skipped))) if args.python_version.startswith('3'): python_version = 3 else: python_version = 2 skip = 'skip/python%d/' % python_version skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which are not supported on python %d: %s' % (skip.rstrip('/'), python_version, ', '.join(skipped))) return exclude def get_integration_docker_filter(args, targets): """ :type args: IntegrationConfig :type targets: tuple[IntegrationTarget] :rtype: list[str] """ exclude = [] if not args.docker_privileged: skip = 'needs/privileged/' skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which require --docker-privileged to run under docker: %s' % (skip.rstrip('/'), ', '.join(skipped))) python_version = 2 # images are expected to default to python 2 unless otherwise specified if args.docker.endswith('py3'): python_version = 3 # docker images ending in 'py3' are expected to default to python 3 if args.docker.endswith(':default'): python_version = 3 # docker images tagged 'default' are expected to default to python 3 if args.python: # specifying a numeric --python option overrides the default python if args.python.startswith('3'): python_version = 3 elif args.python.startswith('2'): python_version = 2 skip = 'skip/python%d/' % python_version skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which are not supported on python %d: %s' % (skip.rstrip('/'), python_version, ', '.join(skipped))) return exclude def get_integration_remote_filter(args, targets): """ :type args: IntegrationConfig :type targets: tuple[IntegrationTarget] :rtype: list[str] """ parts = args.remote.split('/', 1) platform = parts[0] exclude = [] skip = 'skip/%s/' % platform skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which are not supported on %s: %s' % (skip.rstrip('/'), platform, ', '.join(skipped))) python_version = 2 # remotes are expected to default to python 2 skip = 'skip/python%d/' % python_version skipped = [target.name for target in targets if skip in target.aliases] if skipped: exclude.append(skip) display.warning('Excluding tests marked "%s" which are not supported on python %d: %s' % (skip.rstrip('/'), python_version, ', '.join(skipped))) return exclude class EnvironmentDescription(object): """Description of current running environment.""" def __init__(self, args): """Initialize snapshot of environment configuration. :type args: IntegrationConfig """ self.args = args if self.args.explain: self.data = {} return versions = [''] versions += SUPPORTED_PYTHON_VERSIONS versions += list(set(v.split('.')[0] for v in SUPPORTED_PYTHON_VERSIONS)) python_paths = dict((v, find_executable('python%s' % v, required=False)) for v in sorted(versions)) python_versions = dict((v, self.get_version([python_paths[v], '-V'])) for v in sorted(python_paths) if python_paths[v]) pip_paths = dict((v, find_executable('pip%s' % v, required=False)) for v in sorted(versions)) pip_versions = dict((v, self.get_version([pip_paths[v], '--version'])) for v in sorted(pip_paths) if pip_paths[v]) pip_interpreters = dict((v, self.get_shebang(pip_paths[v])) for v in sorted(pip_paths) if pip_paths[v]) known_hosts_hash = self.get_hash(os.path.expanduser('~/.ssh/known_hosts')) self.data = dict( python_paths=python_paths, python_versions=python_versions, pip_paths=pip_paths, pip_versions=pip_versions, pip_interpreters=pip_interpreters, known_hosts_hash=known_hosts_hash, ) def __str__(self): """ :rtype: str """ return json.dumps(self.data, sort_keys=True, indent=4) def validate(self, target_name, throw): """ :type target_name: str :type throw: bool :rtype: bool """ current = EnvironmentDescription(self.args) original_json = str(self) current_json = str(current) if original_json == current_json: return True message = ('Test target "%s" has changed the test environment!\n' 'If these changes are necessary, they must be reverted before the test finishes.\n' '>>> Original Environment\n' '%s\n' '>>> Current Environment\n' '%s' % (target_name, original_json, current_json)) if throw: raise ApplicationError(message) display.error(message) return False @staticmethod def get_version(command): """ :type command: list[str] :rtype: str """ try: stdout, stderr = raw_command(command, capture=True, cmd_verbosity=2) except SubprocessError: return None # all failures are equal, we don't care why it failed, only that it did return (stdout or '').strip() + (stderr or '').strip() @staticmethod def get_shebang(path): """ :type path: str :rtype: str """ with open(path) as script_fd: return script_fd.readline() @staticmethod def get_hash(path): """ :type path: str :rtype: str | None """ if not os.path.exists(path): return None file_hash = hashlib.md5() with open(path, 'rb') as file_fd: file_hash.update(file_fd.read()) return file_hash.hexdigest() class NoChangesDetected(ApplicationWarning): """Exception when change detection was performed, but no changes were found.""" def __init__(self): super(NoChangesDetected, self).__init__('No changes detected.') class NoTestsForChanges(ApplicationWarning): """Exception when changes detected, but no tests trigger as a result.""" def __init__(self): super(NoTestsForChanges, self).__init__('No tests found for detected changes.') class Delegate(Exception): """Trigger command delegation.""" def __init__(self, exclude=None, require=None): """ :type exclude: list[str] | None :type require: list[str] | None """ super(Delegate, self).__init__() self.exclude = exclude or [] self.require = require or [] class AllTargetsSkipped(ApplicationWarning): """All targets skipped.""" def __init__(self): super(AllTargetsSkipped, self).__init__('All targets skipped.')
BTA-BATA/BATA-SOURCE
refs/heads/master
contrib/spendfrom/spendfrom.py
792
#!/usr/bin/env python # # Use the raw transactions API to spend bitcoins received on particular addresses, # and send any change back to that same address. # # Example usage: # spendfrom.py # Lists available funds # spendfrom.py --from=ADDRESS --to=ADDRESS --amount=11.00 # # Assumes it will talk to a bitcoind or Bitcoin-Qt running # on localhost. # # Depends on jsonrpc # from decimal import * import getpass import math import os import os.path import platform import sys import time from jsonrpc import ServiceProxy, json BASE_FEE=Decimal("0.001") def check_json_precision(): """Make sure json library being used does not lose precision converting BTC values""" n = Decimal("20000000.00000003") satoshis = int(json.loads(json.dumps(float(n)))*1.0e8) if satoshis != 2000000000000003: raise RuntimeError("JSON encode/decode loses precision") def determine_db_dir(): """Return the default location of the bitcoin data directory""" if platform.system() == "Darwin": return os.path.expanduser("~/Library/Application Support/Bitcoin/") elif platform.system() == "Windows": return os.path.join(os.environ['APPDATA'], "Bitcoin") return os.path.expanduser("~/.bitcoin") def read_bitcoin_config(dbdir): """Read the bitcoin.conf file from dbdir, returns dictionary of settings""" from ConfigParser import SafeConfigParser class FakeSecHead(object): def __init__(self, fp): self.fp = fp self.sechead = '[all]\n' def readline(self): if self.sechead: try: return self.sechead finally: self.sechead = None else: s = self.fp.readline() if s.find('#') != -1: s = s[0:s.find('#')].strip() +"\n" return s config_parser = SafeConfigParser() config_parser.readfp(FakeSecHead(open(os.path.join(dbdir, "bitcoin.conf")))) return dict(config_parser.items("all")) def connect_JSON(config): """Connect to a bitcoin JSON-RPC server""" testnet = config.get('testnet', '0') testnet = (int(testnet) > 0) # 0/1 in config file, convert to True/False if not 'rpcport' in config: config['rpcport'] = 19332 if testnet else 9332 connect = "http://%s:%s@127.0.0.1:%s"%(config['rpcuser'], config['rpcpassword'], config['rpcport']) try: result = ServiceProxy(connect) # ServiceProxy is lazy-connect, so send an RPC command mostly to catch connection errors, # but also make sure the bitcoind we're talking to is/isn't testnet: if result.getmininginfo()['testnet'] != testnet: sys.stderr.write("RPC server at "+connect+" testnet setting mismatch\n") sys.exit(1) return result except: sys.stderr.write("Error connecting to RPC server at "+connect+"\n") sys.exit(1) def unlock_wallet(bitcoind): info = bitcoind.getinfo() if 'unlocked_until' not in info: return True # wallet is not encrypted t = int(info['unlocked_until']) if t <= time.time(): try: passphrase = getpass.getpass("Wallet is locked; enter passphrase: ") bitcoind.walletpassphrase(passphrase, 5) except: sys.stderr.write("Wrong passphrase\n") info = bitcoind.getinfo() return int(info['unlocked_until']) > time.time() def list_available(bitcoind): address_summary = dict() address_to_account = dict() for info in bitcoind.listreceivedbyaddress(0): address_to_account[info["address"]] = info["account"] unspent = bitcoind.listunspent(0) for output in unspent: # listunspent doesn't give addresses, so: rawtx = bitcoind.getrawtransaction(output['txid'], 1) vout = rawtx["vout"][output['vout']] pk = vout["scriptPubKey"] # This code only deals with ordinary pay-to-bitcoin-address # or pay-to-script-hash outputs right now; anything exotic is ignored. if pk["type"] != "pubkeyhash" and pk["type"] != "scripthash": continue address = pk["addresses"][0] if address in address_summary: address_summary[address]["total"] += vout["value"] address_summary[address]["outputs"].append(output) else: address_summary[address] = { "total" : vout["value"], "outputs" : [output], "account" : address_to_account.get(address, "") } return address_summary def select_coins(needed, inputs): # Feel free to improve this, this is good enough for my simple needs: outputs = [] have = Decimal("0.0") n = 0 while have < needed and n < len(inputs): outputs.append({ "txid":inputs[n]["txid"], "vout":inputs[n]["vout"]}) have += inputs[n]["amount"] n += 1 return (outputs, have-needed) def create_tx(bitcoind, fromaddresses, toaddress, amount, fee): all_coins = list_available(bitcoind) total_available = Decimal("0.0") needed = amount+fee potential_inputs = [] for addr in fromaddresses: if addr not in all_coins: continue potential_inputs.extend(all_coins[addr]["outputs"]) total_available += all_coins[addr]["total"] if total_available < needed: sys.stderr.write("Error, only %f BTC available, need %f\n"%(total_available, needed)); sys.exit(1) # # Note: # Python's json/jsonrpc modules have inconsistent support for Decimal numbers. # Instead of wrestling with getting json.dumps() (used by jsonrpc) to encode # Decimals, I'm casting amounts to float before sending them to bitcoind. # outputs = { toaddress : float(amount) } (inputs, change_amount) = select_coins(needed, potential_inputs) if change_amount > BASE_FEE: # don't bother with zero or tiny change change_address = fromaddresses[-1] if change_address in outputs: outputs[change_address] += float(change_amount) else: outputs[change_address] = float(change_amount) rawtx = bitcoind.createrawtransaction(inputs, outputs) signed_rawtx = bitcoind.signrawtransaction(rawtx) if not signed_rawtx["complete"]: sys.stderr.write("signrawtransaction failed\n") sys.exit(1) txdata = signed_rawtx["hex"] return txdata def compute_amount_in(bitcoind, txinfo): result = Decimal("0.0") for vin in txinfo['vin']: in_info = bitcoind.getrawtransaction(vin['txid'], 1) vout = in_info['vout'][vin['vout']] result = result + vout['value'] return result def compute_amount_out(txinfo): result = Decimal("0.0") for vout in txinfo['vout']: result = result + vout['value'] return result def sanity_test_fee(bitcoind, txdata_hex, max_fee): class FeeError(RuntimeError): pass try: txinfo = bitcoind.decoderawtransaction(txdata_hex) total_in = compute_amount_in(bitcoind, txinfo) total_out = compute_amount_out(txinfo) if total_in-total_out > max_fee: raise FeeError("Rejecting transaction, unreasonable fee of "+str(total_in-total_out)) tx_size = len(txdata_hex)/2 kb = tx_size/1000 # integer division rounds down if kb > 1 and fee < BASE_FEE: raise FeeError("Rejecting no-fee transaction, larger than 1000 bytes") if total_in < 0.01 and fee < BASE_FEE: raise FeeError("Rejecting no-fee, tiny-amount transaction") # Exercise for the reader: compute transaction priority, and # warn if this is a very-low-priority transaction except FeeError as err: sys.stderr.write((str(err)+"\n")) sys.exit(1) def main(): import optparse parser = optparse.OptionParser(usage="%prog [options]") parser.add_option("--from", dest="fromaddresses", default=None, help="addresses to get bitcoins from") parser.add_option("--to", dest="to", default=None, help="address to get send bitcoins to") parser.add_option("--amount", dest="amount", default=None, help="amount to send") parser.add_option("--fee", dest="fee", default="0.0", help="fee to include") parser.add_option("--datadir", dest="datadir", default=determine_db_dir(), help="location of bitcoin.conf file with RPC username/password (default: %default)") parser.add_option("--testnet", dest="testnet", default=False, action="store_true", help="Use the test network") parser.add_option("--dry_run", dest="dry_run", default=False, action="store_true", help="Don't broadcast the transaction, just create and print the transaction data") (options, args) = parser.parse_args() check_json_precision() config = read_bitcoin_config(options.datadir) if options.testnet: config['testnet'] = True bitcoind = connect_JSON(config) if options.amount is None: address_summary = list_available(bitcoind) for address,info in address_summary.iteritems(): n_transactions = len(info['outputs']) if n_transactions > 1: print("%s %.8f %s (%d transactions)"%(address, info['total'], info['account'], n_transactions)) else: print("%s %.8f %s"%(address, info['total'], info['account'])) else: fee = Decimal(options.fee) amount = Decimal(options.amount) while unlock_wallet(bitcoind) == False: pass # Keep asking for passphrase until they get it right txdata = create_tx(bitcoind, options.fromaddresses.split(","), options.to, amount, fee) sanity_test_fee(bitcoind, txdata, amount*Decimal("0.01")) if options.dry_run: print(txdata) else: txid = bitcoind.sendrawtransaction(txdata) print(txid) if __name__ == '__main__': main()
adgaudio/mutable_lru_cache
refs/heads/master
lru_cache_pandas.py
1
import pandas as pd def _pd_hash_on_indexes(arg): """ hash pandas objects to immutable (index, columns) without modifying the objects This hash function uniquely identifies pandas.Series and pandas.DataFrame by (index, columns). This means if values of a column have been overwritten (due to a mutable or "inplace" operation), this cache funtion will ignore the changes and not update the cache. """ if isinstance(arg, (pd.DataFrame, pd.Series)): return (tuple(arg.index), tuple(arg.columns)) else: return arg pd_lru_cache = lru_cache_factory(_pd_hash_on_indexes)
acshi/osf.io
refs/heads/develop
scripts/analytics/run_keen_snapshots.py
6
from framework.celery_tasks import app as celery_app from scripts.analytics.base import BaseAnalyticsHarness from scripts.analytics.addon_snapshot import AddonSnapshot class SnapshotHarness(BaseAnalyticsHarness): @property def analytics_classes(self): return [AddonSnapshot] @celery_app.task(name='scripts.analytics.run_keen_snapshots') def run_main(): SnapshotHarness().main(command_line=False) if __name__ == '__main__': SnapshotHarness().main()
joequery/django
refs/heads/master
django/contrib/sites/requests.py
695
from __future__ import unicode_literals from django.utils.encoding import python_2_unicode_compatible @python_2_unicode_compatible class RequestSite(object): """ A class that shares the primary interface of Site (i.e., it has ``domain`` and ``name`` attributes) but gets its data from a Django HttpRequest object rather than from a database. The save() and delete() methods raise NotImplementedError. """ def __init__(self, request): self.domain = self.name = request.get_host() def __str__(self): return self.domain def save(self, force_insert=False, force_update=False): raise NotImplementedError('RequestSite cannot be saved.') def delete(self): raise NotImplementedError('RequestSite cannot be deleted.')
tstirrat15/exercism-python-responses
refs/heads/master
series/series_test.py
20
"""Tests for the series exercise Implementation note: The slices function should raise a ValueError with a meaningful error message if its length argument doesn't fit the series. """ import unittest from series import slices class SeriesTest(unittest.TestCase): def test_slices_of_one(self): self.assertEqual([[0], [1], [2], [3], [4]], slices("01234", 1)) def test_slices_of_two(self): self.assertEqual([[9, 7], [7, 8], [8, 6], [6, 7], [7, 5], [5, 6], [6, 4]], slices("97867564", 2)) def test_slices_of_three(self): self.assertEqual([[9, 7, 8], [7, 8, 6], [8, 6, 7], [6, 7, 5], [7, 5, 6], [5, 6, 4]], slices("97867564", 3)) def test_slices_of_four(self): self.assertEqual([[0, 1, 2, 3], [1, 2, 3, 4]], slices("01234", 4)) def test_slices_of_five(self): self.assertEqual([[0, 1, 2, 3, 4]], slices("01234", 5)) def test_overly_long_slice(self): with self.assertRaises(ValueError): slices("012", 4) def test_overly_short_slice(self): with self.assertRaises(ValueError): slices("01234", 0) if __name__ == '__main__': unittest.main()
dataxu/ansible
refs/heads/dx-stable-2.5
lib/ansible/modules/cloud/vultr/vr_user.py
23
#!/usr/bin/python # -*- coding: utf-8 -*- # # (c) 2017, René Moser <mail@renemoser.net> # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) from __future__ import (absolute_import, division, print_function) __metaclass__ = type ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ['preview'], 'supported_by': 'community'} DOCUMENTATION = r''' --- module: vr_user short_description: Manages users on Vultr. description: - Create, update and remove users. version_added: "2.5" author: "René Moser (@resmo)" options: name: description: - Name of the user required: true email: description: - Email of the user. - Required if C(state=present). password: description: - Password of the user. - Only considered while creating a user or when C(force=yes). force: description: - Password will only be changed with enforcement. default: no choices: [ yes, no ] api_enabled: description: - Whether the API is enabled or not. default: yes choices: [ yes, no ] acls: description: - List of ACLs this users should have, see U(https://www.vultr.com/api/#user_user_list). - Required if C(state=present). - One or more of the choices list, some depend on each other. choices: - manage_users - subscriptions - provisioning - billing - support - abuse - dns - upgrade state: description: - State of the user. default: present choices: [ present, absent ] extends_documentation_fragment: vultr ''' EXAMPLES = r''' - name: Ensure a user exists local_action: module: vr_user name: john email: john.doe@example.com password: s3cr3t acls: - upgrade - dns - manage_users - subscriptions - upgrade - name: Remove a user local_action: module: vr_user name: john state: absent ''' RETURN = r''' --- vultr_api: description: Response from Vultr API with a few additions/modification returned: success type: complex contains: api_account: description: Account used in the ini file to select the key returned: success type: string sample: default api_timeout: description: Timeout used for the API requests returned: success type: int sample: 60 api_retries: description: Amount of max retries for the API requests returned: success type: int sample: 5 api_endpoint: description: Endpoint used for the API requests returned: success type: string sample: "https://api.vultr.com" vultr_user: description: Response from Vultr API returned: success type: complex contains: id: description: ID of the user. returned: success type: string sample: 5904bc6ed9234 api_key: description: API key of the user. returned: only after resource was created type: string sample: 567E6K567E6K567E6K567E6K567E6K name: description: Name of the user. returned: success type: string sample: john email: description: Email of the user. returned: success type: string sample: "john@exmaple.com" api_enabled: description: Whether the API is enabled or not. returned: success type: bool sample: true acls: description: List of ACLs of the user. returned: success type: list sample: [manage_users, support, upgrade] ''' from ansible.module_utils.basic import AnsibleModule from ansible.module_utils.vultr import ( Vultr, vultr_argument_spec, ) ACLS = [ 'manage_users', 'subscriptions', 'provisioning', 'billing', 'support', 'abuse', 'dns', 'upgrade', ] class AnsibleVultrUser(Vultr): def __init__(self, module): super(AnsibleVultrUser, self).__init__(module, "vultr_user") self.returns = { 'USERID': dict(key='id'), 'name': dict(), 'email': dict(), 'api_enabled': dict(convert_to='bool'), 'acls': dict(), 'api_key': dict() } def _common_args(self): return { 'name': self.module.params.get('name'), 'email': self.module.params.get('email'), 'acls': self.module.params.get('acls'), 'password': self.module.params.get('password'), 'api_enabled': self.get_yes_or_no('api_enabled'), } def get_user(self): users = self.api_query(path="/v1/user/list") for user in users or []: if user.get('name') == self.module.params.get('name'): return user return {} def present_user(self): # Choices with list acls = self.module.params.get('acls') for acl in acls or []: if acl not in ACLS: self.fail_json(msg='value of acls must be one or more of: %s, got: %s' % (ACLS, acls)) user = self.get_user() if not user: user = self._create_user(user) else: user = self._update_user(user) return user def _has_changed(self, user, data): for k, v in data.items(): if k not in user: continue elif isinstance(v, list): for i in v: if i not in user[k]: return True elif data[k] != user[k]: return True return False def _create_user(self, user): self.module.fail_on_missing_params(required_params=['password']) self.result['changed'] = True data = self._common_args() self.result['diff']['before'] = {} self.result['diff']['after'] = data if not self.module.check_mode: user = self.api_query( path="/v1/user/create", method="POST", data=data ) user.update(self.get_user()) return user def _update_user(self, user): data = self._common_args() data.update({ 'USERID': user['USERID'], }) force = self.module.params.get('force') if not force: del data['password'] if force or self._has_changed(user=user, data=data): self.result['changed'] = True self.result['diff']['before'] = user self.result['diff']['after'] = user.copy() self.result['diff']['after'].update(data) if not self.module.check_mode: self.api_query( path="/v1/user/update", method="POST", data=data ) user = self.get_user() return user def absent_user(self): user = self.get_user() if user: self.result['changed'] = True data = { 'USERID': user['USERID'], } self.result['diff']['before'] = user self.result['diff']['after'] = {} if not self.module.check_mode: self.api_query( path="/v1/user/delete", method="POST", data=data ) return user def main(): argument_spec = vultr_argument_spec() argument_spec.update(dict( name=dict(required=True), email=dict(), password=dict(no_log=True), force=dict(type='bool', default=False), api_enabled=dict(type='bool', default=True), acls=dict(type='list', aliases=['acl']), state=dict(choices=['present', 'absent'], default='present'), )) module = AnsibleModule( argument_spec=argument_spec, required_if=[ ('state', 'present', ['email', 'acls']), ], supports_check_mode=True, ) vr_user = AnsibleVultrUser(module) if module.params.get('state') == "absent": user = vr_user.absent_user() else: user = vr_user.present_user() result = vr_user.get_result(user) module.exit_json(**result) if __name__ == '__main__': main()
tumbl3w33d/ansible
refs/heads/devel
test/units/modules/network/fortios/test_fortios_user_setting.py
21
# Copyright 2019 Fortinet, Inc. # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Ansible. If not, see <https://www.gnu.org/licenses/>. # Make coding more python3-ish from __future__ import (absolute_import, division, print_function) __metaclass__ = type import os import json import pytest from mock import ANY from ansible.module_utils.network.fortios.fortios import FortiOSHandler try: from ansible.modules.network.fortios import fortios_user_setting except ImportError: pytest.skip("Could not load required modules for testing", allow_module_level=True) @pytest.fixture(autouse=True) def connection_mock(mocker): connection_class_mock = mocker.patch('ansible.modules.network.fortios.fortios_user_setting.Connection') return connection_class_mock fos_instance = FortiOSHandler(connection_mock) def test_user_setting_creation(mocker): schema_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'success', 'http_method': 'POST', 'http_status': 200} set_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'user_setting': { 'auth_blackout_time': '3', 'auth_ca_cert': 'test_value_4', 'auth_cert': 'test_value_5', 'auth_http_basic': 'enable', 'auth_invalid_max': '7', 'auth_lockout_duration': '8', 'auth_lockout_threshold': '9', 'auth_portal_timeout': '10', 'auth_secure_http': 'enable', 'auth_src_mac': 'enable', 'auth_ssl_allow_renegotiation': 'enable', 'auth_timeout': '14', 'auth_timeout_type': 'idle-timeout', 'auth_type': 'http', 'radius_ses_timeout_act': 'hard-timeout' }, 'vdom': 'root'} is_error, changed, response = fortios_user_setting.fortios_user(input_data, fos_instance) expected_data = { 'auth-blackout-time': '3', 'auth-ca-cert': 'test_value_4', 'auth-cert': 'test_value_5', 'auth-http-basic': 'enable', 'auth-invalid-max': '7', 'auth-lockout-duration': '8', 'auth-lockout-threshold': '9', 'auth-portal-timeout': '10', 'auth-secure-http': 'enable', 'auth-src-mac': 'enable', 'auth-ssl-allow-renegotiation': 'enable', 'auth-timeout': '14', 'auth-timeout-type': 'idle-timeout', 'auth-type': 'http', 'radius-ses-timeout-act': 'hard-timeout' } set_method_mock.assert_called_with('user', 'setting', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert not is_error assert changed assert response['status'] == 'success' assert response['http_status'] == 200 def test_user_setting_creation_fails(mocker): schema_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'error', 'http_method': 'POST', 'http_status': 500} set_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'user_setting': { 'auth_blackout_time': '3', 'auth_ca_cert': 'test_value_4', 'auth_cert': 'test_value_5', 'auth_http_basic': 'enable', 'auth_invalid_max': '7', 'auth_lockout_duration': '8', 'auth_lockout_threshold': '9', 'auth_portal_timeout': '10', 'auth_secure_http': 'enable', 'auth_src_mac': 'enable', 'auth_ssl_allow_renegotiation': 'enable', 'auth_timeout': '14', 'auth_timeout_type': 'idle-timeout', 'auth_type': 'http', 'radius_ses_timeout_act': 'hard-timeout' }, 'vdom': 'root'} is_error, changed, response = fortios_user_setting.fortios_user(input_data, fos_instance) expected_data = { 'auth-blackout-time': '3', 'auth-ca-cert': 'test_value_4', 'auth-cert': 'test_value_5', 'auth-http-basic': 'enable', 'auth-invalid-max': '7', 'auth-lockout-duration': '8', 'auth-lockout-threshold': '9', 'auth-portal-timeout': '10', 'auth-secure-http': 'enable', 'auth-src-mac': 'enable', 'auth-ssl-allow-renegotiation': 'enable', 'auth-timeout': '14', 'auth-timeout-type': 'idle-timeout', 'auth-type': 'http', 'radius-ses-timeout-act': 'hard-timeout' } set_method_mock.assert_called_with('user', 'setting', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert is_error assert not changed assert response['status'] == 'error' assert response['http_status'] == 500 def test_user_setting_idempotent(mocker): schema_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'error', 'http_method': 'DELETE', 'http_status': 404} set_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'user_setting': { 'auth_blackout_time': '3', 'auth_ca_cert': 'test_value_4', 'auth_cert': 'test_value_5', 'auth_http_basic': 'enable', 'auth_invalid_max': '7', 'auth_lockout_duration': '8', 'auth_lockout_threshold': '9', 'auth_portal_timeout': '10', 'auth_secure_http': 'enable', 'auth_src_mac': 'enable', 'auth_ssl_allow_renegotiation': 'enable', 'auth_timeout': '14', 'auth_timeout_type': 'idle-timeout', 'auth_type': 'http', 'radius_ses_timeout_act': 'hard-timeout' }, 'vdom': 'root'} is_error, changed, response = fortios_user_setting.fortios_user(input_data, fos_instance) expected_data = { 'auth-blackout-time': '3', 'auth-ca-cert': 'test_value_4', 'auth-cert': 'test_value_5', 'auth-http-basic': 'enable', 'auth-invalid-max': '7', 'auth-lockout-duration': '8', 'auth-lockout-threshold': '9', 'auth-portal-timeout': '10', 'auth-secure-http': 'enable', 'auth-src-mac': 'enable', 'auth-ssl-allow-renegotiation': 'enable', 'auth-timeout': '14', 'auth-timeout-type': 'idle-timeout', 'auth-type': 'http', 'radius-ses-timeout-act': 'hard-timeout' } set_method_mock.assert_called_with('user', 'setting', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert not is_error assert not changed assert response['status'] == 'error' assert response['http_status'] == 404 def test_user_setting_filter_foreign_attributes(mocker): schema_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'success', 'http_method': 'POST', 'http_status': 200} set_method_mock = mocker.patch('ansible.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'user_setting': { 'random_attribute_not_valid': 'tag', 'auth_blackout_time': '3', 'auth_ca_cert': 'test_value_4', 'auth_cert': 'test_value_5', 'auth_http_basic': 'enable', 'auth_invalid_max': '7', 'auth_lockout_duration': '8', 'auth_lockout_threshold': '9', 'auth_portal_timeout': '10', 'auth_secure_http': 'enable', 'auth_src_mac': 'enable', 'auth_ssl_allow_renegotiation': 'enable', 'auth_timeout': '14', 'auth_timeout_type': 'idle-timeout', 'auth_type': 'http', 'radius_ses_timeout_act': 'hard-timeout' }, 'vdom': 'root'} is_error, changed, response = fortios_user_setting.fortios_user(input_data, fos_instance) expected_data = { 'auth-blackout-time': '3', 'auth-ca-cert': 'test_value_4', 'auth-cert': 'test_value_5', 'auth-http-basic': 'enable', 'auth-invalid-max': '7', 'auth-lockout-duration': '8', 'auth-lockout-threshold': '9', 'auth-portal-timeout': '10', 'auth-secure-http': 'enable', 'auth-src-mac': 'enable', 'auth-ssl-allow-renegotiation': 'enable', 'auth-timeout': '14', 'auth-timeout-type': 'idle-timeout', 'auth-type': 'http', 'radius-ses-timeout-act': 'hard-timeout' } set_method_mock.assert_called_with('user', 'setting', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert not is_error assert changed assert response['status'] == 'success' assert response['http_status'] == 200
jandom/rdkit
refs/heads/master
rdkit/sping/Pyart/__init__.py
18
# sping:: pyart from pidPyart import *
uzh/vm-mad
refs/heads/master
vmmad/simul.py
1
#! /usr/bin/env python # """ Simulate an `Orchestrator` run given some parameters. """ # Copyright (C) 2011, 2012 ETH Zurich and University of Zurich. All rights reserved. # # Authors: # Christian Panse <cp@fgcz.ethz.ch> # Riccardo Murri <riccardo.murri@gmail.com> # Tyanko Aleksiev <tyanko.alexiev@gmail.com> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from __future__ import absolute_import __docformat__ = 'reStructuredText' __version__ = "1.0dev (SVN $Revision$)" # stdlib imports import argparse from copy import copy import csv import os import sys import time import types # local imports from vmmad import log from vmmad.batchsys.replay import JobsFromFile from vmmad.provider.libcloud import DummyCloud from vmmad.orchestrator import Orchestrator, JobInfo, VmInfo class OrchestratorSimulation(Orchestrator, DummyCloud): def __init__(self, max_vms, max_delta, max_idle, startup_delay, output_file, csv_file, start_time, time_interval, cluster_size): # Convert starting time to UNIX time if start_time is not None and isinstance(start_time, types.StringTypes): start_time = time.mktime(time.strptime(start_time, "%Y-%m-%dT%H:%M:%S" )) # implement the `Cloud` interface to simulate a cloud provider DummyCloud.__init__(self, '1', '1') # init the Orchestrator part, using `self` as cloud provider and batch system interface Orchestrator.__init__( self, cloud=self, batchsys=JobsFromFile(csv_file, self.time, start_time), max_vms=max_vms, max_delta=max_delta, vm_start_timeout=time_interval*max(startup_delay, 10)) # make cluster nodes already available at start self.cluster_size = cluster_size for n in xrange(cluster_size): # NOTE: use `Orchestrator.new_vm` here, as `self.new_vm` creates a *real VM* nodeid = ('clusternode-%d' % n) node = Orchestrator.new_vm(self, vmid=nodeid, state=VmInfo.READY, nodename=nodeid, ever_running=True) self.vms[nodeid] = node # Set simulation settings self.max_idle = max_idle self.startup_delay = startup_delay self.output_file = open(output_file, "wb") self.writer = csv.writer(self.output_file, delimiter=',') self.writer.writerow( ['#TimeStamp', 'Pending Jobs', 'Running Jobs', 'Started VMs', 'Idle VMS']) self.time_interval = int(time_interval) self._next_row = None # info about running VMs self._vmid = 0 # no running jobs at the onset self._running = 0 # if `starting_time` has not been set, then use earliest job # submission time as starting point self.starting_time = self.batchsys.start_time - self.time_interval log.info("Starting simulation at %s", time.strftime('%Y-%m-%dT%H:%M:%S', time.gmtime(self.starting_time))) def update_job_status(self): # do regular work Orchestrator.update_job_status(self) # count running jobs self._running = len([ job for job in self.jobs.itervalues() if job.state == JobInfo.RUNNING ]) # simulate 'ready' notification from VMs starting_vms = [ vm for vm in self.vms.values() if vm.state == VmInfo.STARTING ] for vm in starting_vms: # we use `vm.last_idle` as a countdown to the `READY` state for VMs: # it is initialized to `-startup_delay` and incremented at every pass if vm.last_idle >= 0: nodename = ("vm-%s" % vm.vmid) self.vm_is_ready(vm.auth, nodename) else: vm.last_idle += 1 # simulate SGE scheduler starting a new job ready_vms = [ vm for vm in self.vms.values() if vm.state == VmInfo.READY ] for vm in ready_vms: if not vm.jobs: if not self.candidates: break job = self.candidates.pop() job.state = JobInfo.RUNNING job.exec_node_name = vm.nodename job.running_at = self.time() self._running += 1 vm.jobs.add(job.jobid) log.info("Job %s just started running on node %s (%s).", job.jobid, vm.vmid, vm.nodename) def before(self): # XXX: this only works with `JobsFromFile`! if len(self.jobs) == 0 and len(self.batchsys.future_jobs) == 0: log.info("No more jobs, stopping here") self.output_file.close() sys.exit(0) vms = [ vm for vm in self.vms.values() if not vm.ever_running ] vm_count = len(vms) starting_vm_count = len([ vm for vm in vms if vm.state == VmInfo.STARTING ]) ready_vms_count = len([ vm for vm in vms if vm.state == VmInfo.READY ]) stopping_vms_count = len([ vm for vm in vms if vm.state == VmInfo.STOPPING ]) idle_vm_count = len([ vm for vm in vms if vm.last_idle > 0 ]) self.writer.writerow( # timestamp, pending jobs, running jobs, started VMs, idle VMs, [self.time(), len(self.candidates), self._running, len(self.vms)-self.cluster_size, idle_vm_count]) log.info( "At time %d: pending jobs %d, running jobs %d, total started VMs %d," " starting VMs %d, ready VMs %d, idle VMs %d, stopping VMs %d", self.time(), len(self.candidates), self._running, len(self.vms), starting_vm_count, ready_vms_count, idle_vm_count, stopping_vms_count) def time(self): """ Return the current time in the simulation as UNIX epoch. """ return self.starting_time + self.cycle * self.time_interval def new_vm(self, **attrs): return Orchestrator.new_vm(self, ever_running=False, last_idle=-self.startup_delay) ## ## policy implementation interface ## def is_cloud_candidate(self, job): # every job is a candidate in this simulation return True def is_new_vm_needed(self): if len(self.candidates) > 2 * len(self.vms): return True def can_vm_be_stopped(self, vm): if (not vm.ever_running and (vm.last_idle > self.max_idle) and len(vm.jobs) == 0): return True else: return False ## ## (fake) cloud provider interface ## def start_vm(self, vm): DummyCloud.start_vm(self, vm) def update_vm_status(self, vms): DummyCloud.update_vm_status(self, vms) def stop_vm(self, vm): assert not vm.ever_running, ( "Request to stop VM %s which is marked as 'ever running'" % vm.vmid) DummyCloud.stop_vm(self, vm) return True if "__main__" == __name__: parser = argparse.ArgumentParser(description='Simulates a cloud orchestrator') parser.add_argument('--max-vms', '-mv', metavar='N', dest="max_vms", default=10, type=int, help="Maximum number of VMs to be started, default is %(default)s") parser.add_argument('--max-delta', '-md', metavar='N', dest="max_delta", default=1, type=int, help="Cap the number of VMs that can be started or stopped in a single orchestration cycle. Default is %(default)d.") parser.add_argument('--max-idle', '-mi', metavar='NUM_SECS', dest="max_idle", default=7200, type=int, help="Maximum idle time (in seconds) before swithing off a VM, default is %(default)s") parser.add_argument('--startup-delay', '-s', metavar='NUM_SECS', dest="startup_delay", default=60, type=int, help="Time (in seconds) delay before a started VM is READY. Default is %(default)s") parser.add_argument('--csv-file', '-csvf', metavar='String', dest="csv_file", default="accounting.csv", help="File containing the CSV information, %(default)s") parser.add_argument('--output-file', '-o', metavar='String', dest="output_file", default="main_sim.txt", help="File name where the output of the simulation will be stored, %(default)s") parser.add_argument('--cluster-size', '-cs', metavar='NUM_CPUS', dest="cluster_size", default="20", type=int, help="Number of VMs, used for the simulation of real available cluster: %(default)s") parser.add_argument('--start-time', '-stime', metavar='String', dest="start_time", default=-1, help="Start time for the simulation, default: %(default)s") parser.add_argument('--time-interval', '-timei', metavar='NUM_SECS', type=int, dest="time_interval", default="3600", help="UNIX interval in seconds used as parsing interval for the jobs in the CSV file, default: %(default)s") parser.add_argument('--version', '-V', action='version', version=("%(prog)s version " + __version__)) args = parser.parse_args() OrchestratorSimulation(args.max_vms, args.max_delta, args.max_idle, args.startup_delay, args.output_file, args.csv_file, args.start_time, args.time_interval, args.cluster_size).run(0)
apark263/tensorflow
refs/heads/master
tensorflow/contrib/tensorrt/python/trt_convert_test.py
1
# Copyright 2018 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Utilities to test TF-TensorRT integration.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import os # pylint: disable=unused-import from tensorflow.compiler.tf2tensorrt.python.ops import trt_ops # pylint: enable=unused-import from tensorflow.contrib.tensorrt.python import trt_convert from tensorflow.core.framework import graph_pb2 from tensorflow.core.protobuf import config_pb2 from tensorflow.core.protobuf import rewriter_config_pb2 from tensorflow.python.framework import dtypes from tensorflow.python.framework import graph_util from tensorflow.python.framework import importer from tensorflow.python.framework import ops from tensorflow.python.framework import test_util from tensorflow.python.ops import array_ops from tensorflow.python.ops import variables from tensorflow.python.platform import test from tensorflow.python.saved_model import builder from tensorflow.python.saved_model import loader from tensorflow.python.saved_model import signature_constants from tensorflow.python.saved_model import signature_def_utils from tensorflow.python.saved_model import tag_constants from tensorflow.python.saved_model import utils from tensorflow.python.tools import saved_model_utils class TrtConvertTest(test_util.TensorFlowTestCase): """Class to test Tensorflow-TensorRT integration python API.""" def testGetTensorrtRewriterConfig(self): """Test case for trt_convert.get_tensorrt_rewriter_config().""" rewriter_cfg = trt_convert.get_tensorrt_rewriter_config( rewriter_config=None, max_batch_size=128, max_workspace_size_bytes=1234, precision_mode="INT8", minimum_segment_size=10, is_dynamic_op=True, maximum_cached_engines=2, cached_engine_batches=[1, 128]) self.assertEqual(["constfold", "layout", "constfold"], rewriter_cfg.optimizers) self.assertEqual(rewriter_config_pb2.RewriterConfig.ONE, rewriter_cfg.meta_optimizer_iterations) trt_optimizer = None for optimizer in rewriter_cfg.custom_optimizers: if optimizer.name == "TensorRTOptimizer": self.assertTrue(trt_optimizer is None) trt_optimizer = optimizer self.assertTrue(trt_optimizer is not None) for key in [ "minimum_segment_size", "max_batch_size", "is_dynamic_op", "max_workspace_size_bytes", "precision_mode", "maximum_cached_engines", "cached_engine_batches" ]: self.assertTrue(key in trt_optimizer.parameter_map) self.assertEqual(10, trt_optimizer.parameter_map["minimum_segment_size"].i) self.assertEqual(128, trt_optimizer.parameter_map["max_batch_size"].i) self.assertEqual(True, trt_optimizer.parameter_map["is_dynamic_op"].b) self.assertEqual(1234, trt_optimizer.parameter_map["max_workspace_size_bytes"].i) self.assertEqual( trt_convert._to_bytes("INT8"), trt_optimizer.parameter_map["precision_mode"].s) self.assertEqual(2, trt_optimizer.parameter_map["maximum_cached_engines"].i) self.assertEqual( [1, 128], trt_optimizer.parameter_map["cached_engine_batches"].list.i) def _GetConfigProto(self): """Get ConfigProto for session creation.""" config = config_pb2.ConfigProto( gpu_options=config_pb2.GPUOptions(allow_growth=True)) return config def _GetGraph(self): """Get the graph for testing.""" g = ops.Graph() with g.as_default(): with g.device("/GPU:0"): inp = array_ops.placeholder( dtype=dtypes.float32, shape=[None, 1, 1], name="input") var = variables.VariableV1([[[1.0]]], dtype=dtypes.float32, name="v1") add = inp + var.value() mul = inp * add add = mul + add out = array_ops.identity(add, name="output") return g, var, inp, out def _GetGraphDef(self): """Get the graph def for testing.""" g, var, _, _ = self._GetGraph() with self.session(graph=g, config=self._GetConfigProto()) as sess: sess.run(var.initializer) graph_def = graph_util.convert_variables_to_constants( sess, g.as_graph_def(add_shapes=True), ["output"]) node_name_to_op = {node.name: node.op for node in graph_def.node} self.assertEqual({ "v1": "Const", "v1/read": "Identity", "input": "Placeholder", "add": "Add", "mul": "Mul", "add_1": "Add", "output": "Identity" }, node_name_to_op) return graph_def def _WriteInputSavedModel(self, input_saved_model_dir): """Write the saved model as an input for testing.""" g, var, inp, out = self._GetGraph() signature_def = signature_def_utils.build_signature_def( inputs={"myinput": utils.build_tensor_info(inp)}, outputs={"myoutput": utils.build_tensor_info(out)}, method_name=signature_constants.PREDICT_METHOD_NAME) saved_model_builder = builder.SavedModelBuilder(input_saved_model_dir) with self.session(graph=g, config=self._GetConfigProto()) as sess: sess.run(var.initializer) saved_model_builder.add_meta_graph_and_variables( sess, [tag_constants.SERVING], signature_def_map={"mypredict": signature_def}) saved_model_builder.save() def _TestCreateInferenceGraph(self, input_saved_model_dir=None, output_saved_model_dir=None): """General method to test trt_convert.create_inference_graph().""" input_graph_def = None if input_saved_model_dir else self._GetGraphDef() output_graph_def = trt_convert.create_inference_graph( input_graph_def, ["output"], input_saved_model_dir=input_saved_model_dir, output_saved_model_dir=output_saved_model_dir, session_config=self._GetConfigProto()) graph_defs_to_verify = [output_graph_def] if output_saved_model_dir is not None: saved_model_graph_def = saved_model_utils.get_meta_graph_def( output_saved_model_dir, tag_constants.SERVING).graph_def self.assertTrue(isinstance(saved_model_graph_def, graph_pb2.GraphDef)) graph_defs_to_verify.append(saved_model_graph_def) for graph_def in graph_defs_to_verify: node_name_to_op = {node.name: node.op for node in graph_def.node} self.assertEqual({ "input": "Placeholder", "TRTEngineOp_0": "TRTEngineOp", "output": "Identity" }, node_name_to_op) def testCreateInferenceGraph_BasicConversion(self): """Test case for trt_convert.create_inference_graph().""" if not trt_convert.is_tensorrt_enabled(): return # Use GraphDef as input. self._TestCreateInferenceGraph() # Use SavedModel as input. tmp_dir = self.get_temp_dir() input_saved_model_dir = os.path.join(tmp_dir, "in_dir1") output_saved_model_dir = os.path.join(tmp_dir, "out_dir1") self._WriteInputSavedModel(input_saved_model_dir) self._TestCreateInferenceGraph(input_saved_model_dir, output_saved_model_dir) def _TestRun(self, sess, batch_size, expect_engine_is_run): trt_convert.clear_test_values("") result = sess.run("output:0", feed_dict={"input:0": [[[1.0]]] * batch_size}) self.assertAllEqual([[[4.0]]] * batch_size, result) execute_engine_test_value = ("done" if expect_engine_is_run else "") execute_native_segment_test_value = ("" if expect_engine_is_run else "done") self.assertEqual( execute_engine_test_value, trt_convert.get_test_value("TRTEngineOp_0:ExecuteTrtEngine")) self.assertEqual( execute_native_segment_test_value, trt_convert.get_test_value("TRTEngineOp_0:ExecuteNativeSegment")) def testCreateInferenceGraph_MinimumSegmentSize(self): if not trt_convert.is_tensorrt_enabled(): return output_graph_def = trt_convert.create_inference_graph( self._GetGraphDef(), ["output"], minimum_segment_size=5, is_dynamic_op=False) node_name_to_op = {node.name: node.op for node in output_graph_def.node} self.assertEqual({ "v1/read": "Const", "input": "Placeholder", "add": "Add", "mul": "Mul", "add_1": "Add", "output": "Identity" }, node_name_to_op) def testCreateInferenceGraph_DynamicOp(self): if not trt_convert.is_tensorrt_enabled(): return trt_convert.enable_test_value() tmp_dir = self.get_temp_dir() input_saved_model_dir = os.path.join(tmp_dir, "in_dir2") output_saved_model_dir = os.path.join(tmp_dir, "out_dir2") self._WriteInputSavedModel(input_saved_model_dir) output_graph_def = trt_convert.create_inference_graph( None, None, is_dynamic_op=True, maximum_cached_engines=2, input_saved_model_dir=input_saved_model_dir, output_saved_model_dir=output_saved_model_dir, session_config=self._GetConfigProto()) # Test the output GraphDef. with ops.Graph().as_default(): importer.import_graph_def(output_graph_def, name="") with self.test_session(config=self._GetConfigProto()) as sess: # Run with batch size 1, a new engine is created and cached. self._TestRun(sess, 1, True) # Run with batch size 2, a new engine is created and cached. self._TestRun(sess, 2, True) # Run with batch size 3, since the number of cached engines has reached # the max, it should evict an old engine and create a new one. self._TestRun(sess, 3, True) # Test the output SavedModel with ops.Graph().as_default(): with self.test_session(config=self._GetConfigProto()) as sess: loader.load(sess, [tag_constants.SERVING], output_saved_model_dir) # Run with batch size 1, a new engine is created and cached. self._TestRun(sess, 1, True) # Run with batch size 2, a new engine is created and cached. self._TestRun(sess, 2, True) # Run with batch size 3, since the number of cached engines has reached # the max, it should evict an old engine and create a new one. self._TestRun(sess, 3, True) def testCreateInferenceGraph_StaticOp(self): if not trt_convert.is_tensorrt_enabled(): return trt_convert.enable_test_value() tmp_dir = self.get_temp_dir() input_saved_model_dir = os.path.join(tmp_dir, "in_dir3") output_saved_model_dir = os.path.join(tmp_dir, "out_dir3") self._WriteInputSavedModel(input_saved_model_dir) output_graph_def = trt_convert.create_inference_graph( None, None, max_batch_size=1, is_dynamic_op=False, maximum_cached_engines=2, # This is noop, added just for testing. input_saved_model_dir=input_saved_model_dir, output_saved_model_dir=output_saved_model_dir, session_config=self._GetConfigProto()) # Test the output GraphDef. with ops.Graph().as_default(): importer.import_graph_def(output_graph_def, name="") with self.test_session(config=self._GetConfigProto()) as sess: # Run with batch size 1, the default engine embedded in the graphdef # will be used. self._TestRun(sess, 1, True) # Run with batch size 2, which exceed the max_batch_size, it should fall # back to TF function. self._TestRun(sess, 2, False) # Test the output SavedModel with ops.Graph().as_default(): with self.test_session(config=self._GetConfigProto()) as sess: loader.load(sess, [tag_constants.SERVING], output_saved_model_dir) # Run with batch size 1, the default engine embedded in the graphdef # will be used. self._TestRun(sess, 1, True) # Run with batch size 2, which exceed the max_batch_size, it should fall # back to TF function. self._TestRun(sess, 2, False) if __name__ == "__main__": test.main()
eloquence/unisubs
refs/heads/staging
apps/webdriver_testing/pages/site_pages/teams_dir_page.py
5
#!/usr/bin/env python import time from nose.tools import assert_true, assert_false from webdriver_testing.pages.site_pages import UnisubsPage class TeamsDirPage(UnisubsPage): """ Search page is the main search page stub. Watch Page and Search Results page """ _URL = "teams/" _SEARCH = "form.search input[name='q']" _SORT = "span.sort_label" _SORT_OPTION = "div.sort_button ul li a[href*='%s']" _TEAM = "ul.listing li" _TEAM_LINK = 'h3 a[href*=%s]' _TEAM_NAME = 'a' _TEAM_MEMBERS = 'ul.actions h4' _TEAM_VIDEOS = 'ul.actions li:nth-child(2)' _TEAM_DESCRIPTION = 'p' _TEAM_DESCRIPTOR = '.descriptor' _NO_MATCHES = 'p.empty' _NO_MATCH_TEXT = 'Sorry, no teams found.' _TEAM_BY_POSITION = "ul.listing li:nth-child(%d)" _INVITE_ERROR = 'div#error h1' #YOUR TEAMS TAB _YOUR_URL = "teams/my/" _LEAVE_URL = "teams/leave_team/%s/" _LEAVE = "a#leave" def open_teams_page(self): self.open_page(self._URL) def _team_elem(self, team): """Given the team's text name, return the css locator string. """ self.wait_for_element_present(self._TEAM + " " + self._TEAM_NAME) teams = self.browser.find_elements_by_css_selector(self._TEAM) for el in teams: team_el = el.find_element_by_css_selector(self._TEAM_NAME) print teams.index(el) if team == team_el.text: return self._TEAM_BY_POSITION % (teams.index(el) + 1) def team_search(self, search_term): self.clear_text(self._SEARCH) self.submit_form_text_by_css(self._SEARCH, search_term) def search_has_no_matches(self): if self.is_text_present(self._NO_MATCHES, self._NO_MATCH_TEXT): return True def sort(self, order): """Sort the teams. """ sort_orders = ['date', 'name', 'members'] assert_true(order in sort_orders, "unknown value for order, expected one of %s" % sort_orders) self.open_page("teams/?o=%s" % order) def first_team(self): return self.teams_on_page()[0] def last_team(self): return self.teams_on_page()[-1:][0] def all_team_elements(self): team_elements = self.browser.find_elements_by_css_selector(self._TEAM) return team_elements def team_el(self, team): team_elements = self.all_team_elements() for el in team_elements: if el.find_element_by_css_selector(self._TEAM_NAME).text == team: return el else: self.fail("Did not find the team named %s on the page" % team) def members(self, team): """Return the number of members displayed for a team. """ element = self.team_el(team) members = element.find_element_by_css_selector(self._TEAM_MEMBERS).text return int(members.split()[0]) def videos(self, team): """Return the number of videos displayed for a team. """ element = self.team_el(team) videos = element.find_element_by_css_selector(self._TEAM_VIDEOS).text return int(videos.split()[0]) def teams_on_page(self): """Return a list of teams displayed on the page. """ teams_list = [] team_name_els = self.browser.find_elements_by_css_selector( " ".join([self._TEAM, self._TEAM_NAME])) for el in team_name_els: teams_list.append(el.text) return teams_list def team_displayed(self, team): team_list = self.teams_on_page() if team in team_list: return True else: return "Team {0} not found in the list of teams {1}".format(team, team_list) def marked_private(self, team): """Return True if a team is marked private. """ self.team_search(team) descriptor_text = self.get_text_by_css(self._TEAM_DESCRIPTOR) if descriptor_text == "Private": return True def open_team_with_link(self, team_slug): """Open a specific team page, given the team slug. """ self.click_by_css(self._TEAM_LINK % team_slug) # YOUR TEAMS TAB SPECIFIC def open_my_teams_page(self): """Open the teams/my/ url. """ self.open_page(self._YOUR_URL) def open_my_team(self, team=None): if self._YOUR_URL not in self.browser.current_url: self.open_my_teams_page() if not team: first_team = self._TEAM, self._TEAM_NAME self.click_by_css(first_team) else: team_el = self._team_elem(team) team = team_el.find_element_by_css_selector(self._TEAM_NAME) team.click() def leave_team(self, team_stub): self.open_page(self._LEAVE_URL % team_stub) def leave_team_successful(self): self.wait_for_element_present(self._SUCCESS_MESSAGE) if self.is_text_present(self._SUCCESS_MESSAGE, 'You have left this team.'): return True def leave_team_failed(self): if self.is_text_present(self._ERROR_MESSAGE, 'You are the last owner of this team.'): return True def _hover_team(self, team): team_el = self._team_elem(team) self.hover_by_css(team_el) def leave_present(self, team): leave_link = False self._hover_team(team) if self.is_element_visible(self._LEAVE): leave_link = True return leave_link def click_leave_link(self, team): self.click_item_after_hover(self._team_elem(team), self._LEAVE) self.handle_js_alert('accept') def invite_error(self): return self.get_text_by_css(self._INVITE_ERROR)
ogajduse/spacewalk
refs/heads/master
client/rhel/rhn-client-tools/src/up2date_client/debUtils.py
5
# Client code for Update Agent # Copyright (c) 2011--2016 Red Hat, Inc. Distributed under GPLv2. # # Author: Simon Lukasik # Lukas Durfina # import os import apt import gettext t = gettext.translation('rhn-client-tools', fallback=True) # Python 3 translations don't have a ugettext method if not hasattr(t, 'ugettext'): t.ugettext = t.gettext _ = t.ugettext # FIXME: After Debian bug 187019 is resolved def verifyPackages(packages): cache = apt.Cache() missing_packages = [] for package in packages: pkg = cache[package[0]] if pkg == None or not pkg.is_installed: missing_packages.append(package) return [], missing_packages def parseVRE(version): epoch = '' release = 'X' if version.find(':') != -1: epoch, version = version.split(':') if version.find('-') != -1: tmp = version.split('-') version = '-'.join(tmp[:-1]) release = tmp[-1] return version, release, epoch def installTime(pkg_name, pkg_arch): dir = '/var/lib/dpkg/info' files = [ '%s.list' % pkg_name, '%s:%s.list' % (pkg_name, pkg_arch) ] for f in files: path = os.path.join(dir,f) if os.path.isfile(path): return os.path.getmtime(path) return None #FIXME: Using Apt cache might not be an ultimate solution. # It could be better to parse /var/lib/dpkg/status manually. # Apt cache might not contain all the packages. def getInstalledPackageList(msgCallback = None, progressCallback = None, getArch=None, getInfo = None): """ Return list of packages. Package is dict with following keys: name, epoch, version, release and optionaly arch. """ if msgCallback != None: msgCallback(_("Getting list of packages installed on the system")) cache = apt.Cache() total = 0 for pkg in cache: if pkg.installed != None: total += 1 count = 0 pkg_list = [] for pkg in cache: if pkg.installed == None: continue version, release, epoch = parseVRE(pkg.installed.version) package = { 'name': pkg.name, 'epoch': epoch, 'version': version, 'release': release, 'arch': pkg.installed.architecture + '-deb', 'installtime': installTime(pkg.name, pkg.installed.architecture) } pkg_list.append(package) if progressCallback != None: progressCallback(count, total) count = count + 1 pkg_list.sort() return pkg_list def setDebugVerbosity(): pass
blaswan/dbn-cifar-10
refs/heads/master
code/logistic_regression.py
1
""" This tutorial introduces logistic regression using Theano. Logistic regression is a probabilistic, linear classifier. It is parametrized by a weight matrix :math:`W` and a bias vector :math:`b`. Classification is done by projecting data points onto a set of hyperplanes, the distance to which is used to determine a class membership probability. Mathematically, this can be written as: .. math:: P(Y=i|x, W,b) &= softmax_i(W x + b) \\ &= \frac {e^{W_i x + b_i}} {\sum_j e^{W_j x + b_j}} The output of the model or prediction is then done by taking the argmax of the vector whose i'th element is P(Y=i|x). .. math:: y_{pred} = argmax_i P(Y=i|x,W,b) References: - textbooks: "Pattern Recognition and Machine Learning" - Christopher M. Bishop, section 4.3.2 """ __docformat__ = 'restructedtext en' import numpy import theano import theano.tensor as T class LogisticRegression(object): """Multi-class Logistic Regression Class The logistic regression is fully described by a weight matrix :math:`W` and bias vector :math:`b`. Classification is done by projecting data points onto a set of hyperplanes, the distance to which is used to determine a class membership probability. """ def __init__(self, input, n_in, n_out): """ Initialize the parameters of the logistic regression :type input: theano.tensor.TensorType :param input: symbolic variable that describes the input of the architecture (one minibatch) :type n_in: int :param n_in: number of input units, the dimension of the space in which the datapoints lie :type n_out: int :param n_out: number of output units, the dimension of the space in which the labels lie """ # start-snippet-1 # initialize with 0 the weights W as a matrix of shape (n_in, n_out) self.W = theano.shared( value=numpy.zeros( (n_in, n_out), dtype=theano.config.floatX ), name='W', borrow=True ) # initialize the baises b as a vector of n_out 0s self.b = theano.shared( value=numpy.zeros( (n_out,), dtype=theano.config.floatX ), name='b', borrow=True ) # symbolic expression for computing the matrix of class-membership # probabilities # Where: # W is a matrix where column-k represent the separation hyper plain for # class-k # x is a matrix where row-j represents input training sample-j # b is a vector where element-k represent the free parameter of hyper # plain-k self.p_y_given_x = T.nnet.softmax(T.dot(input, self.W) + self.b) # symbolic description of how to compute prediction as class whose # probability is maximal self.y_pred = T.argmax(self.p_y_given_x, axis=1) # end-snippet-1 # parameters of the model self.params = [self.W, self.b] def negative_log_likelihood(self, y): """Return the mean of the negative log-likelihood of the prediction of this model under a given target distribution. .. math:: \frac{1}{|\mathcal{D}|} \mathcal{L} (\theta=\{W,b\}, \mathcal{D}) = \frac{1}{|\mathcal{D}|} \sum_{i=0}^{|\mathcal{D}|} \log(P(Y=y^{(i)}|x^{(i)}, W,b)) \\ \ell (\theta=\{W,b\}, \mathcal{D}) :type y: theano.tensor.TensorType :param y: corresponds to a vector that gives for each example the correct label Note: we use the mean instead of the sum so that the learning rate is less dependent on the batch size """ # start-snippet-2 # y.shape[0] is (symbolically) the number of rows in y, i.e., # number of examples (call it n) in the minibatch # T.arange(y.shape[0]) is a symbolic vector which will contain # [0,1,2,... n-1] T.log(self.p_y_given_x) is a matrix of # Log-Probabilities (call it LP) with one row per example and # one column per class LP[T.arange(y.shape[0]),y] is a vector # v containing [LP[0,y[0]], LP[1,y[1]], LP[2,y[2]], ..., # LP[n-1,y[n-1]]] and T.mean(LP[T.arange(y.shape[0]),y]) is # the mean (across minibatch examples) of the elements in v, # i.e., the mean log-likelihood across the minibatch. return -T.mean(T.log(self.p_y_given_x)[T.arange(y.shape[0]), y]) # end-snippet-2 def errors(self, y): """Return a float representing the number of errors in the minibatch over the total number of examples of the minibatch ; zero one loss over the size of the minibatch :type y: theano.tensor.TensorType :param y: corresponds to a vector that gives for each example the correct label """ # check if y has same dimension of y_pred if y.ndim != self.y_pred.ndim: raise TypeError( 'y should have the same shape as self.y_pred', ('y', y.type, 'y_pred', self.y_pred.type) ) # check if y is of the correct datatype if y.dtype.startswith('int'): # the T.neq operator returns a vector of 0s and 1s, where 1 # represents a mistake in prediction return T.mean(T.neq(self.y_pred, y)) else: raise NotImplementedError()
learningequality/kolibri
refs/heads/develop
kolibri/core/device/test/test_api.py
2
import os import platform import sys from collections import namedtuple import mock from django.conf import settings from django.core.exceptions import ValidationError from django.core.urlresolvers import reverse from mock import patch from morango.models import DatabaseIDModel from morango.models import InstanceIDModel from rest_framework import status from rest_framework.test import APITestCase import kolibri from kolibri.core.auth.constants.role_kinds import ADMIN from kolibri.core.auth.models import Facility from kolibri.core.auth.models import FacilityDataset from kolibri.core.auth.models import FacilityUser from kolibri.core.auth.models import Role from kolibri.core.auth.test.helpers import clear_process_cache from kolibri.core.auth.test.helpers import create_superuser from kolibri.core.auth.test.helpers import provision_device from kolibri.core.auth.test.test_api import FacilityFactory from kolibri.core.auth.test.test_api import FacilityUserFactory from kolibri.core.device.models import DevicePermissions from kolibri.core.device.models import DeviceSettings DUMMY_PASSWORD = "password" class DeviceProvisionTestCase(APITestCase): def setUp(self): clear_process_cache() superuser_data = {"username": "superuser", "password": "password"} facility_data = {"name": "Wilson Elementary"} preset_data = "nonformal" dataset_data = { "learner_can_edit_username": True, "learner_can_edit_name": True, "learner_can_edit_password": True, "learner_can_sign_up": True, "learner_can_delete_account": True, "learner_can_login_with_no_password": False, } settings = {} allow_guest_access = True language_id = "en" def _default_provision_data(self): return { "device_name": None, "superuser": self.superuser_data, "facility": self.facility_data, "preset": self.preset_data, "settings": self.settings, "language_id": self.language_id, "allow_guest_access": self.allow_guest_access, } def _post_deviceprovision(self, data): return self.client.post( reverse("kolibri:core:deviceprovision"), data, format="json" ) def test_personal_setup_defaults(self): data = self._default_provision_data() data["preset"] = "informal" # Client should pass an empty Dict for settings data["settings"] = {} self._post_deviceprovision(data) settings = FacilityDataset.objects.get() self.assertEqual(settings.learner_can_edit_username, True) self.assertEqual(settings.learner_can_edit_name, True) self.assertEqual(settings.learner_can_edit_password, True) self.assertEqual(settings.learner_can_sign_up, True) self.assertEqual(settings.learner_can_delete_account, True) self.assertEqual(settings.learner_can_login_with_no_password, False) self.assertEqual(settings.show_download_button_in_learn, True) device_settings = DeviceSettings.objects.get() self.assertEqual(device_settings.allow_guest_access, True) def test_cannot_post_if_provisioned(self): provision_device() data = self._default_provision_data() response = self._post_deviceprovision(data) self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) def test_superuser_created(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertEqual( FacilityUser.objects.get().username, self.superuser_data["username"] ) def test_superuser_password_set_correctly(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertTrue( FacilityUser.objects.get().check_password(self.superuser_data["password"]) ) def test_superuser_device_permissions_created(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertEqual( DevicePermissions.objects.get(), FacilityUser.objects.get().devicepermissions, ) def test_facility_created(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertEqual(Facility.objects.get().name, self.facility_data["name"]) def test_admin_role_created(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertEqual(Role.objects.get().kind, ADMIN) def test_facility_role_created(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertEqual(Role.objects.get().collection.name, self.facility_data["name"]) def test_dataset_set_created(self): data = self._default_provision_data() self._post_deviceprovision(data) self.assertEqual( FacilityDataset.objects.get().learner_can_edit_username, self.dataset_data["learner_can_edit_username"], ) self.assertEqual( FacilityDataset.objects.get().learner_can_edit_name, self.dataset_data["learner_can_edit_name"], ) self.assertEqual( FacilityDataset.objects.get().learner_can_edit_password, self.dataset_data["learner_can_edit_password"], ) self.assertEqual( FacilityDataset.objects.get().learner_can_sign_up, self.dataset_data["learner_can_sign_up"], ) self.assertEqual( FacilityDataset.objects.get().learner_can_delete_account, self.dataset_data["learner_can_delete_account"], ) self.assertEqual( FacilityDataset.objects.get().learner_can_login_with_no_password, self.dataset_data["learner_can_login_with_no_password"], ) def test_device_settings_created(self): data = self._default_provision_data() self.assertEqual(DeviceSettings.objects.count(), 0) self._post_deviceprovision(data) self.assertEqual(DeviceSettings.objects.count(), 1) def test_device_settings_values(self): data = self._default_provision_data() data["allow_guest_access"] = False self._post_deviceprovision(data) device_settings = DeviceSettings.objects.get() self.assertEqual(device_settings.default_facility, Facility.objects.get()) self.assertFalse(device_settings.allow_guest_access) self.assertFalse(device_settings.allow_peer_unlisted_channel_import) self.assertTrue(device_settings.allow_learner_unassigned_resource_access) class DeviceSettingsTestCase(APITestCase): @classmethod def setUpTestData(cls): cls.settings = { "language_id": "en", "allow_guest_access": False, "allow_peer_unlisted_channel_import": True, "allow_learner_unassigned_resource_access": False, } cls.facility = FacilityFactory.create() provision_device(language_id="es", default_facility=cls.facility) cls.superuser = create_superuser(cls.facility) cls.user = FacilityUserFactory.create(facility=cls.facility) def setUp(self): super(DeviceSettingsTestCase, self).setUp() self.client.login( username=self.superuser.username, password=DUMMY_PASSWORD, facility=self.facility, ) def test_requires_authentication(self): self.client.logout() response = self.client.post( reverse("kolibri:core:devicesettings"), self.settings, format="json" ) self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) def test_cannot_post(self): response = self.client.post( reverse("kolibri:core:devicesettings"), self.settings, format="json" ) self.assertEqual(response.status_code, status.HTTP_405_METHOD_NOT_ALLOWED) def test_cannot_put(self): response = self.client.put( reverse("kolibri:core:devicesettings"), self.settings, format="json" ) self.assertEqual(response.status_code, status.HTTP_405_METHOD_NOT_ALLOWED) def test_patch(self): device_settings = DeviceSettings.objects.get() self.assertEqual("es", device_settings.language_id) self.assertTrue(device_settings.allow_guest_access) self.assertFalse(device_settings.allow_peer_unlisted_channel_import) self.assertTrue(device_settings.allow_learner_unassigned_resource_access) self.client.patch( reverse("kolibri:core:devicesettings"), self.settings, format="json" ) device_settings.refresh_from_db() self.assertEqual("en", device_settings.language_id) self.assertFalse(device_settings.allow_guest_access) self.assertTrue(device_settings.allow_peer_unlisted_channel_import) self.assertFalse(device_settings.allow_learner_unassigned_resource_access) class DevicePermissionsTestCase(APITestCase): @classmethod def setUpTestData(cls): provision_device() cls.facility = FacilityFactory.create() cls.superuser = create_superuser(cls.facility) cls.user = FacilityUserFactory.create(facility=cls.facility) def setUp(self): self.client.login( username=self.superuser.username, password=DUMMY_PASSWORD, facility=self.facility, ) def test_superuser_delete_own_permissions(self): response = self.client.delete( reverse( "kolibri:core:devicepermissions-detail", kwargs={"pk": self.superuser.devicepermissions.pk}, ), format="json", ) self.assertEqual(response.status_code, 403) def test_superuser_update_own_permissions(self): response = self.client.patch( reverse( "kolibri:core:devicepermissions-detail", kwargs={"pk": self.superuser.devicepermissions.pk}, ), {"is_superuser": False}, format="json", ) self.assertEqual(response.status_code, 403) class FreeSpaceTestCase(APITestCase): def setUp(self): provision_device() self.facility = FacilityFactory.create() self.superuser = create_superuser(self.facility) self.user = FacilityUserFactory.create(facility=self.facility) self.client.login( username=self.superuser.username, password=DUMMY_PASSWORD, facility=self.facility, ) def test_posix_freespace(self): if not sys.platform.startswith("win"): with mock.patch("kolibri.utils.system.os.statvfs") as os_statvfs_mock: statvfs_result = namedtuple("statvfs_result", ["f_frsize", "f_bavail"]) os_statvfs_mock.return_value = statvfs_result(f_frsize=1, f_bavail=2) response = self.client.get( reverse("kolibri:core:freespace"), {"path": "test"} ) os_statvfs_mock.assert_called_with(os.path.realpath("test")) self.assertEqual(response.data, {"freespace": 2}) def test_win_freespace_fail(self): if sys.platform.startswith("win"): ctypes_mock = mock.MagicMock() with mock.patch.dict("sys.modules", ctypes=ctypes_mock): ctypes_mock.windll.kernel32.GetDiskFreeSpaceExW.return_value = 0 ctypes_mock.winError.side_effect = OSError try: self.client.get(reverse("kolibri:core:freespace"), {"path": "test"}) except OSError: # check if ctypes.winError() has been called ctypes_mock.winError.assert_called_with() class DeviceInfoTestCase(APITestCase): @classmethod def setUpTestData(cls): provision_device() DatabaseIDModel.objects.create() cls.facility = FacilityFactory.create() cls.superuser = create_superuser(cls.facility) def setUp(self): self.client.login( username=self.superuser.username, password=DUMMY_PASSWORD, facility=self.facility, ) def test_has_version(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(response.data["version"], kolibri.__version__) def test_urls(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertFalse(len(response.data["urls"]) == 0) for url in response.data["urls"]: # Make sure each url is a valid link self.assertTrue(url.startswith("http://")) @patch( "kolibri.core.device.api.get_urls", return_value=(1, ["http://127.0.0.1:8000", "http://kolibri.com"]), ) def test_no_localhost_urls_when_others_available(self, get_urls_mock): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(len(response.data["urls"]), 1) self.assertEqual(response.data["urls"][0], "http://kolibri.com") @patch( "kolibri.core.device.api.get_urls", return_value=(1, ["http://127.0.0.1:8000"]) ) def test_localhost_urls_when_no_others_available(self, get_urls_mock): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(len(response.data["urls"]), 1) self.assertEqual(response.data["urls"][0], "http://127.0.0.1:8000") def test_database_path(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") db_engine = settings.DATABASES["default"]["ENGINE"] db_path = response.data["database_path"] if db_engine.endswith("sqlite3"): self.assertEqual(db_path, settings.DATABASES["default"]["NAME"]) elif db_engine.endswith("postgresql"): self.assertEqual(db_path, "postgresql") else: self.assertEqual(db_path, "unknown") def test_os(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(response.data["os"], platform.platform()) def test_device_id(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual( response.data["device_id"], InstanceIDModel.get_or_create_current_instance()[0].id, ) def test_time_zone(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertTrue(response.data["server_timezone"], settings.TIME_ZONE) def test_free_space(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(type(response.data["content_storage_free_space"]), int) def test_superuser_permissions(self): response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(response.status_code, 200) def test_user_permissions(self): self.user = FacilityUserFactory.create(facility=self.facility) self.client.logout() self.client.login( username=self.user.username, password=DUMMY_PASSWORD, facility=self.facility ) response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(response.status_code, 403) def test_user_with_permissions(self): self.user = FacilityUserFactory.create(facility=self.facility) DevicePermissions.objects.create(user=self.user, can_manage_content=True) self.client.logout() self.client.login( username=self.user.username, password=DUMMY_PASSWORD, facility=self.facility ) response = self.client.get(reverse("kolibri:core:deviceinfo"), format="json") self.assertEqual(response.status_code, 200) class DeviceNameTestCase(APITestCase): @classmethod def setUpTestData(cls): cls.device_name = {"name": "test device"} cls.facility = FacilityFactory.create() provision_device(language_id="es", default_facility=cls.facility) cls.superuser = create_superuser(cls.facility) cls.user = FacilityUserFactory.create(facility=cls.facility) def setUp(self): super(DeviceNameTestCase, self).setUp() self.client.login( username=self.superuser.username, password=DUMMY_PASSWORD, facility=self.facility, ) def test_requires_authentication(self): self.client.logout() response = self.client.post( reverse("kolibri:core:devicename"), self.device_name, format="json" ) self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) def test_existing_device_name(self): response = self.client.get(reverse("kolibri:core:devicename")) self.assertEqual( response.data["name"], InstanceIDModel.get_or_create_current_instance()[0].hostname, ) def test_patch(self): device_settings = DeviceSettings.objects.get() self.assertEqual( device_settings.name, InstanceIDModel.get_or_create_current_instance()[0].hostname, ) response = self.client.patch( reverse("kolibri:core:devicename"), self.device_name, format="json" ) self.assertEqual(response.data, self.device_name) device_settings.refresh_from_db() self.assertEqual(device_settings.name, self.device_name["name"]) self.assertNotEqual( device_settings.name, InstanceIDModel.get_or_create_current_instance()[0].hostname, ) def test_device_name_max_length(self): with self.assertRaises(ValidationError): exceeds_max_length_name = {"name": "a" * 60} self.client.patch( reverse("kolibri:core:devicename"), exceeds_max_length_name, format="json", )
loli/sklearn-ensembletrees
refs/heads/master
sklearn/datasets/mlcomp.py
5
# Copyright (c) 2010 Olivier Grisel <olivier.grisel@ensta.org> # License: BSD 3 clause """Glue code to load http://mlcomp.org data as a scikit.learn dataset""" import os import numbers from sklearn.datasets.base import load_files def _load_document_classification(dataset_path, metadata, set_=None, **kwargs): if set_ is not None: dataset_path = os.path.join(dataset_path, set_) return load_files(dataset_path, metadata.get('description'), **kwargs) LOADERS = { 'DocumentClassification': _load_document_classification, # TODO: implement the remaining domain formats } def load_mlcomp(name_or_id, set_="raw", mlcomp_root=None, **kwargs): """Load a datasets as downloaded from http://mlcomp.org Parameters ---------- name_or_id : the integer id or the string name metadata of the MLComp dataset to load `set_` : select the portion to load: 'train', 'test' or 'raw' mlcomp_root : the filesystem path to the root folder where MLComp datasets are stored, if mlcomp_root is None, the MLCOMP_DATASETS_HOME environment variable is looked up instead. **kwargs : domain specific kwargs to be passed to the dataset loader. Returns ------- data : Bunch Dictionary-like object, the interesting attributes are: 'filenames', the files holding the raw to learn, 'target', the classification labels (integer index), 'target_names', the meaning of the labels, and 'DESCR', the full description of the dataset. Note on the lookup process: depending on the type of name_or_id, will choose between integer id lookup or metadata name lookup by looking at the unzipped archives and metadata file. TODO: implement zip dataset loading too """ if mlcomp_root is None: try: mlcomp_root = os.environ['MLCOMP_DATASETS_HOME'] except KeyError: raise ValueError("MLCOMP_DATASETS_HOME env variable is undefined") mlcomp_root = os.path.expanduser(mlcomp_root) mlcomp_root = os.path.abspath(mlcomp_root) mlcomp_root = os.path.normpath(mlcomp_root) if not os.path.exists(mlcomp_root): raise ValueError("Could not find folder: " + mlcomp_root) # dataset lookup if isinstance(name_or_id, numbers.Integral): # id lookup dataset_path = os.path.join(mlcomp_root, str(name_or_id)) else: # assume name based lookup dataset_path = None expected_name_line = "name: " + name_or_id for dataset in os.listdir(mlcomp_root): metadata_file = os.path.join(mlcomp_root, dataset, 'metadata') if not os.path.exists(metadata_file): continue with open(metadata_file) as f: for line in f: if line.strip() == expected_name_line: dataset_path = os.path.join(mlcomp_root, dataset) break if dataset_path is None: raise ValueError("Could not find dataset with metadata line: " + expected_name_line) # loading the dataset metadata metadata = dict() metadata_file = os.path.join(dataset_path, 'metadata') if not os.path.exists(metadata_file): raise ValueError(dataset_path + ' is not a valid MLComp dataset') with open(metadata_file) as f: for line in f: if ":" in line: key, value = line.split(":", 1) metadata[key.strip()] = value.strip() format = metadata.get('format', 'unknow') loader = LOADERS.get(format) if loader is None: raise ValueError("No loader implemented for format: " + format) return loader(dataset_path, metadata, set_=set_, **kwargs)
Innovahn/cybex
refs/heads/master
addons/web/controllers/main.py
20
# -*- coding: utf-8 -*- import ast import base64 import csv import functools import glob import itertools import jinja2 import logging import operator import datetime import hashlib import os import re import simplejson import sys import time import urllib2 import zlib from xml.etree import ElementTree from cStringIO import StringIO import babel.messages.pofile import werkzeug.utils import werkzeug.wrappers try: import xlwt except ImportError: xlwt = None import openerp import openerp.modules.registry from openerp.addons.base.ir.ir_qweb import AssetsBundle, QWebTemplateNotFound from openerp.modules import get_module_resource from openerp.tools import topological_sort from openerp.tools.translate import _ from openerp import http from openerp.http import request, serialize_exception as _serialize_exception _logger = logging.getLogger(__name__) if hasattr(sys, 'frozen'): # When running on compiled windows binary, we don't have access to package loader. path = os.path.realpath(os.path.join(os.path.dirname(__file__), '..', 'views')) loader = jinja2.FileSystemLoader(path) else: loader = jinja2.PackageLoader('openerp.addons.web', "views") env = jinja2.Environment(loader=loader, autoescape=True) env.filters["json"] = simplejson.dumps # 1 week cache for asset bundles as advised by Google Page Speed BUNDLE_MAXAGE = 60 * 60 * 24 * 7 #---------------------------------------------------------- # OpenERP Web helpers #---------------------------------------------------------- db_list = http.db_list db_monodb = http.db_monodb def serialize_exception(f): @functools.wraps(f) def wrap(*args, **kwargs): try: return f(*args, **kwargs) except Exception, e: _logger.exception("An exception occured during an http request") se = _serialize_exception(e) error = { 'code': 200, 'message': "Odoo Server Error", 'data': se } return werkzeug.exceptions.InternalServerError(simplejson.dumps(error)) return wrap def redirect_with_hash(*args, **kw): """ .. deprecated:: 8.0 Use the ``http.redirect_with_hash()`` function instead. """ return http.redirect_with_hash(*args, **kw) def abort_and_redirect(url): r = request.httprequest response = werkzeug.utils.redirect(url, 302) response = r.app.get_response(r, response, explicit_session=False) werkzeug.exceptions.abort(response) def ensure_db(redirect='/web/database/selector'): # This helper should be used in web client auth="none" routes # if those routes needs a db to work with. # If the heuristics does not find any database, then the users will be # redirected to db selector or any url specified by `redirect` argument. # If the db is taken out of a query parameter, it will be checked against # `http.db_filter()` in order to ensure it's legit and thus avoid db # forgering that could lead to xss attacks. db = request.params.get('db') # Ensure db is legit if db and db not in http.db_filter([db]): db = None if db and not request.session.db: # User asked a specific database on a new session. # That mean the nodb router has been used to find the route # Depending on installed module in the database, the rendering of the page # may depend on data injected by the database route dispatcher. # Thus, we redirect the user to the same page but with the session cookie set. # This will force using the database route dispatcher... r = request.httprequest url_redirect = r.base_url if r.query_string: # Can't use werkzeug.wrappers.BaseRequest.url with encoded hashes: # https://github.com/amigrave/werkzeug/commit/b4a62433f2f7678c234cdcac6247a869f90a7eb7 url_redirect += '?' + r.query_string response = werkzeug.utils.redirect(url_redirect, 302) request.session.db = db abort_and_redirect(url_redirect) # if db not provided, use the session one if not db and request.session.db and http.db_filter([request.session.db]): db = request.session.db # if no database provided and no database in session, use monodb if not db: db = db_monodb(request.httprequest) # if no db can be found til here, send to the database selector # the database selector will redirect to database manager if needed if not db: werkzeug.exceptions.abort(werkzeug.utils.redirect(redirect, 303)) # always switch the session to the computed db if db != request.session.db: request.session.logout() abort_and_redirect(request.httprequest.url) request.session.db = db def module_installed(): # Candidates module the current heuristic is the /static dir loadable = http.addons_manifest.keys() modules = {} # Retrieve database installed modules # TODO The following code should move to ir.module.module.list_installed_modules() Modules = request.session.model('ir.module.module') domain = [('state','=','installed'), ('name','in', loadable)] for module in Modules.search_read(domain, ['name', 'dependencies_id']): modules[module['name']] = [] deps = module.get('dependencies_id') if deps: deps_read = request.session.model('ir.module.module.dependency').read(deps, ['name']) dependencies = [i['name'] for i in deps_read] modules[module['name']] = dependencies sorted_modules = topological_sort(modules) return sorted_modules def module_installed_bypass_session(dbname): loadable = http.addons_manifest.keys() modules = {} try: registry = openerp.modules.registry.RegistryManager.get(dbname) with registry.cursor() as cr: m = registry.get('ir.module.module') # TODO The following code should move to ir.module.module.list_installed_modules() domain = [('state','=','installed'), ('name','in', loadable)] ids = m.search(cr, 1, [('state','=','installed'), ('name','in', loadable)]) for module in m.read(cr, 1, ids, ['name', 'dependencies_id']): modules[module['name']] = [] deps = module.get('dependencies_id') if deps: deps_read = registry.get('ir.module.module.dependency').read(cr, 1, deps, ['name']) dependencies = [i['name'] for i in deps_read] modules[module['name']] = dependencies except Exception,e: pass sorted_modules = topological_sort(modules) return sorted_modules def module_boot(db=None): server_wide_modules = openerp.conf.server_wide_modules or ['web'] serverside = [] dbside = [] for i in server_wide_modules: if i in http.addons_manifest: serverside.append(i) monodb = db or db_monodb() if monodb: dbside = module_installed_bypass_session(monodb) dbside = [i for i in dbside if i not in serverside] addons = serverside + dbside return addons def concat_xml(file_list): """Concatenate xml files :param list(str) file_list: list of files to check :returns: (concatenation_result, checksum) :rtype: (str, str) """ checksum = hashlib.new('sha1') if not file_list: return '', checksum.hexdigest() root = None for fname in file_list: with open(fname, 'rb') as fp: contents = fp.read() checksum.update(contents) fp.seek(0) xml = ElementTree.parse(fp).getroot() if root is None: root = ElementTree.Element(xml.tag) #elif root.tag != xml.tag: # raise ValueError("Root tags missmatch: %r != %r" % (root.tag, xml.tag)) for child in xml.getchildren(): root.append(child) return ElementTree.tostring(root, 'utf-8'), checksum.hexdigest() def fs2web(path): """convert FS path into web path""" return '/'.join(path.split(os.path.sep)) def manifest_glob(extension, addons=None, db=None, include_remotes=False): if addons is None: addons = module_boot(db=db) else: addons = addons.split(',') r = [] for addon in addons: manifest = http.addons_manifest.get(addon, None) if not manifest: continue # ensure does not ends with / addons_path = os.path.join(manifest['addons_path'], '')[:-1] globlist = manifest.get(extension, []) for pattern in globlist: if pattern.startswith(('http://', 'https://', '//')): if include_remotes: r.append((None, pattern)) else: for path in glob.glob(os.path.normpath(os.path.join(addons_path, addon, pattern))): r.append((path, fs2web(path[len(addons_path):]))) return r def manifest_list(extension, mods=None, db=None, debug=None): """ list ressources to load specifying either: mods: a comma separated string listing modules db: a database name (return all installed modules in that database) """ if debug is not None: _logger.warning("openerp.addons.web.main.manifest_list(): debug parameter is deprecated") files = manifest_glob(extension, addons=mods, db=db, include_remotes=True) return [wp for _fp, wp in files] def get_last_modified(files): """ Returns the modification time of the most recently modified file provided :param list(str) files: names of files to check :return: most recent modification time amongst the fileset :rtype: datetime.datetime """ files = list(files) if files: return max(datetime.datetime.fromtimestamp(os.path.getmtime(f)) for f in files) return datetime.datetime(1970, 1, 1) def make_conditional(response, last_modified=None, etag=None, max_age=0): """ Makes the provided response conditional based upon the request, and mandates revalidation from clients Uses Werkzeug's own :meth:`ETagResponseMixin.make_conditional`, after setting ``last_modified`` and ``etag`` correctly on the response object :param response: Werkzeug response :type response: werkzeug.wrappers.Response :param datetime.datetime last_modified: last modification date of the response content :param str etag: some sort of checksum of the content (deep etag) :return: the response object provided :rtype: werkzeug.wrappers.Response """ response.cache_control.must_revalidate = True response.cache_control.max_age = max_age if last_modified: response.last_modified = last_modified if etag: response.set_etag(etag) return response.make_conditional(request.httprequest) def login_and_redirect(db, login, key, redirect_url='/web'): request.session.authenticate(db, login, key) return set_cookie_and_redirect(redirect_url) def set_cookie_and_redirect(redirect_url): redirect = werkzeug.utils.redirect(redirect_url, 303) redirect.autocorrect_location_header = False return redirect def login_redirect(): url = '/web/login?' if request.debug: url += 'debug&' return """<html><head><script> window.location = '%sredirect=' + encodeURIComponent(window.location); </script></head></html> """ % (url,) def load_actions_from_ir_values(key, key2, models, meta): Values = request.session.model('ir.values') actions = Values.get(key, key2, models, meta, request.context) return [(id, name, clean_action(action)) for id, name, action in actions] def clean_action(action): action.setdefault('flags', {}) action_type = action.setdefault('type', 'ir.actions.act_window_close') if action_type == 'ir.actions.act_window': return fix_view_modes(action) return action # I think generate_views,fix_view_modes should go into js ActionManager def generate_views(action): """ While the server generates a sequence called "views" computing dependencies between a bunch of stuff for views coming directly from the database (the ``ir.actions.act_window model``), it's also possible for e.g. buttons to return custom view dictionaries generated on the fly. In that case, there is no ``views`` key available on the action. Since the web client relies on ``action['views']``, generate it here from ``view_mode`` and ``view_id``. Currently handles two different cases: * no view_id, multiple view_mode * single view_id, single view_mode :param dict action: action descriptor dictionary to generate a views key for """ view_id = action.get('view_id') or False if isinstance(view_id, (list, tuple)): view_id = view_id[0] # providing at least one view mode is a requirement, not an option view_modes = action['view_mode'].split(',') if len(view_modes) > 1: if view_id: raise ValueError('Non-db action dictionaries should provide ' 'either multiple view modes or a single view ' 'mode and an optional view id.\n\n Got view ' 'modes %r and view id %r for action %r' % ( view_modes, view_id, action)) action['views'] = [(False, mode) for mode in view_modes] return action['views'] = [(view_id, view_modes[0])] def fix_view_modes(action): """ For historical reasons, OpenERP has weird dealings in relation to view_mode and the view_type attribute (on window actions): * one of the view modes is ``tree``, which stands for both list views and tree views * the choice is made by checking ``view_type``, which is either ``form`` for a list view or ``tree`` for an actual tree view This methods simply folds the view_type into view_mode by adding a new view mode ``list`` which is the result of the ``tree`` view_mode in conjunction with the ``form`` view_type. TODO: this should go into the doc, some kind of "peculiarities" section :param dict action: an action descriptor :returns: nothing, the action is modified in place """ if not action.get('views'): generate_views(action) if action.pop('view_type', 'form') != 'form': return action if 'view_mode' in action: action['view_mode'] = ','.join( mode if mode != 'tree' else 'list' for mode in action['view_mode'].split(',')) action['views'] = [ [id, mode if mode != 'tree' else 'list'] for id, mode in action['views'] ] return action def _local_web_translations(trans_file): messages = [] try: with open(trans_file) as t_file: po = babel.messages.pofile.read_po(t_file) except Exception: return for x in po: if x.id and x.string and "openerp-web" in x.auto_comments: messages.append({'id': x.id, 'string': x.string}) return messages def xml2json_from_elementtree(el, preserve_whitespaces=False): """ xml2json-direct Simple and straightforward XML-to-JSON converter in Python New BSD Licensed http://code.google.com/p/xml2json-direct/ """ res = {} if el.tag[0] == "{": ns, name = el.tag.rsplit("}", 1) res["tag"] = name res["namespace"] = ns[1:] else: res["tag"] = el.tag res["attrs"] = {} for k, v in el.items(): res["attrs"][k] = v kids = [] if el.text and (preserve_whitespaces or el.text.strip() != ''): kids.append(el.text) for kid in el: kids.append(xml2json_from_elementtree(kid, preserve_whitespaces)) if kid.tail and (preserve_whitespaces or kid.tail.strip() != ''): kids.append(kid.tail) res["children"] = kids return res def content_disposition(filename): filename = filename.encode('utf8') escaped = urllib2.quote(filename) browser = request.httprequest.user_agent.browser version = int((request.httprequest.user_agent.version or '0').split('.')[0]) if browser == 'msie' and version < 9: return "attachment; filename=%s" % escaped elif browser == 'safari': return "attachment; filename=%s" % filename else: return "attachment; filename*=UTF-8''%s" % escaped #---------------------------------------------------------- # OpenERP Web web Controllers #---------------------------------------------------------- class Home(http.Controller): @http.route('/', type='http', auth="none") def index(self, s_action=None, db=None, **kw): return http.local_redirect('/web', query=request.params, keep_hash=True) @http.route('/web', type='http', auth="none") def web_client(self, s_action=None, **kw): ensure_db() if request.session.uid: if kw.get('redirect'): return werkzeug.utils.redirect(kw.get('redirect'), 303) if not request.uid: request.uid = request.session.uid menu_data = request.registry['ir.ui.menu'].load_menus(request.cr, request.uid, context=request.context) return request.render('web.webclient_bootstrap', qcontext={'menu_data': menu_data}) else: return login_redirect() @http.route('/web/login', type='http', auth="none") def web_login(self, redirect=None, **kw): ensure_db() if request.httprequest.method == 'GET' and redirect and request.session.uid: return http.redirect_with_hash(redirect) if not request.uid: request.uid = openerp.SUPERUSER_ID values = request.params.copy() if not redirect: redirect = '/web?' + request.httprequest.query_string values['redirect'] = redirect try: values['databases'] = http.db_list() except openerp.exceptions.AccessDenied: values['databases'] = None if request.httprequest.method == 'POST': old_uid = request.uid uid = request.session.authenticate(request.session.db, request.params['login'], request.params['password']) if uid is not False: return http.redirect_with_hash(redirect) request.uid = old_uid values['error'] = "Wrong login/password" return request.render('web.login', values) @http.route('/login', type='http', auth="none") def login(self, db, login, key, redirect="/web", **kw): if not http.db_filter([db]): return werkzeug.utils.redirect('/', 303) return login_and_redirect(db, login, key, redirect_url=redirect) @http.route([ '/web/js/<xmlid>', '/web/js/<xmlid>/<version>', ], type='http', auth='public') def js_bundle(self, xmlid, version=None, **kw): try: bundle = AssetsBundle(xmlid) except QWebTemplateNotFound: return request.not_found() response = request.make_response(bundle.js(), [('Content-Type', 'application/javascript')]) return make_conditional(response, bundle.last_modified, max_age=BUNDLE_MAXAGE) @http.route([ '/web/css/<xmlid>', '/web/css/<xmlid>/<version>', ], type='http', auth='public') def css_bundle(self, xmlid, version=None, **kw): try: bundle = AssetsBundle(xmlid) except QWebTemplateNotFound: return request.not_found() response = request.make_response(bundle.css(), [('Content-Type', 'text/css')]) return make_conditional(response, bundle.last_modified, max_age=BUNDLE_MAXAGE) class WebClient(http.Controller): @http.route('/web/webclient/csslist', type='json', auth="none") def csslist(self, mods=None): return manifest_list('css', mods=mods) @http.route('/web/webclient/jslist', type='json', auth="none") def jslist(self, mods=None): return manifest_list('js', mods=mods) @http.route('/web/webclient/qweb', type='http', auth="none") def qweb(self, mods=None, db=None): files = [f[0] for f in manifest_glob('qweb', addons=mods, db=db)] last_modified = get_last_modified(files) if request.httprequest.if_modified_since and request.httprequest.if_modified_since >= last_modified: return werkzeug.wrappers.Response(status=304) content, checksum = concat_xml(files) return make_conditional( request.make_response(content, [('Content-Type', 'text/xml')]), last_modified, checksum) @http.route('/web/webclient/bootstrap_translations', type='json', auth="none") def bootstrap_translations(self, mods): """ Load local translations from *.po files, as a temporary solution until we have established a valid session. This is meant only for translating the login page and db management chrome, using the browser's language. """ # For performance reasons we only load a single translation, so for # sub-languages (that should only be partially translated) we load the # main language PO instead - that should be enough for the login screen. lang = request.lang.split('_')[0] translations_per_module = {} for addon_name in mods: if http.addons_manifest[addon_name].get('bootstrap'): addons_path = http.addons_manifest[addon_name]['addons_path'] f_name = os.path.join(addons_path, addon_name, "i18n", lang + ".po") if not os.path.exists(f_name): continue translations_per_module[addon_name] = {'messages': _local_web_translations(f_name)} return {"modules": translations_per_module, "lang_parameters": None} @http.route('/web/webclient/translations', type='json', auth="none") def translations(self, mods=None, lang=None): request.disable_db = False uid = openerp.SUPERUSER_ID if mods is None: m = request.registry.get('ir.module.module') mods = [x['name'] for x in m.search_read(request.cr, uid, [('state','=','installed')], ['name'])] if lang is None: lang = request.context["lang"] res_lang = request.registry.get('res.lang') ids = res_lang.search(request.cr, uid, [("code", "=", lang)]) lang_params = None if ids: lang_params = res_lang.read(request.cr, uid, ids[0], ["direction", "date_format", "time_format", "grouping", "decimal_point", "thousands_sep"]) # Regional languages (ll_CC) must inherit/override their parent lang (ll), but this is # done server-side when the language is loaded, so we only need to load the user's lang. ir_translation = request.registry.get('ir.translation') translations_per_module = {} messages = ir_translation.search_read(request.cr, uid, [('module','in',mods),('lang','=',lang), ('comments','like','openerp-web'),('value','!=',False), ('value','!=','')], ['module','src','value','lang'], order='module') for mod, msg_group in itertools.groupby(messages, key=operator.itemgetter('module')): translations_per_module.setdefault(mod,{'messages':[]}) translations_per_module[mod]['messages'].extend({'id': m['src'], 'string': m['value']} \ for m in msg_group) return {"modules": translations_per_module, "lang_parameters": lang_params} @http.route('/web/webclient/version_info', type='json', auth="none") def version_info(self): return openerp.service.common.exp_version() @http.route('/web/tests', type='http', auth="none") def index(self, mod=None, **kwargs): return request.render('web.qunit_suite') class Proxy(http.Controller): @http.route('/web/proxy/load', type='json', auth="none") def load(self, path): """ Proxies an HTTP request through a JSON request. It is strongly recommended to not request binary files through this, as the result will be a binary data blob as well. :param path: actual request path :return: file content """ from werkzeug.test import Client from werkzeug.wrappers import BaseResponse base_url = request.httprequest.base_url return Client(request.httprequest.app, BaseResponse).get(path, base_url=base_url).data class Database(http.Controller): @http.route('/web/database/selector', type='http', auth="none") def selector(self, **kw): try: dbs = http.db_list() if not dbs: return http.local_redirect('/web/database/manager') except openerp.exceptions.AccessDenied: dbs = False return env.get_template("database_selector.html").render({ 'databases': dbs, 'debug': request.debug, }) @http.route('/web/database/manager', type='http', auth="none") def manager(self, **kw): # TODO: migrate the webclient's database manager to server side views request.session.logout() return env.get_template("database_manager.html").render({ 'modules': simplejson.dumps(module_boot()), }) @http.route('/web/database/get_list', type='json', auth="none") def get_list(self): # TODO change js to avoid calling this method if in monodb mode try: return http.db_list() except openerp.exceptions.AccessDenied: monodb = db_monodb() if monodb: return [monodb] raise @http.route('/web/database/create', type='json', auth="none") def create(self, fields): params = dict(map(operator.itemgetter('name', 'value'), fields)) db_created = request.session.proxy("db").create_database( params['super_admin_pwd'], params['db_name'], bool(params.get('demo_data')), params['db_lang'], params['create_admin_pwd']) if db_created: request.session.authenticate(params['db_name'], 'admin', params['create_admin_pwd']) return db_created @http.route('/web/database/duplicate', type='json', auth="none") def duplicate(self, fields): params = dict(map(operator.itemgetter('name', 'value'), fields)) duplicate_attrs = ( params['super_admin_pwd'], params['db_original_name'], params['db_name'], ) return request.session.proxy("db").duplicate_database(*duplicate_attrs) @http.route('/web/database/drop', type='json', auth="none") def drop(self, fields): password, db = operator.itemgetter( 'drop_pwd', 'drop_db')( dict(map(operator.itemgetter('name', 'value'), fields))) try: if request.session.proxy("db").drop(password, db): return True else: return False except openerp.exceptions.AccessDenied: return {'error': 'AccessDenied', 'title': 'Drop Database'} except Exception: return {'error': _('Could not drop database !'), 'title': _('Drop Database')} @http.route('/web/database/backup', type='http', auth="none") def backup(self, backup_db, backup_pwd, token): try: db_dump = base64.b64decode( request.session.proxy("db").dump(backup_pwd, backup_db)) filename = "%(db)s_%(timestamp)s.dump" % { 'db': backup_db, 'timestamp': datetime.datetime.utcnow().strftime( "%Y-%m-%d_%H-%M-%SZ") } return request.make_response(db_dump, [('Content-Type', 'application/octet-stream; charset=binary'), ('Content-Disposition', content_disposition(filename))], {'fileToken': token} ) except Exception, e: return simplejson.dumps([[],[{'error': openerp.tools.ustr(e), 'title': _('Backup Database')}]]) @http.route('/web/database/restore', type='http', auth="none") def restore(self, db_file, restore_pwd, new_db, mode): try: copy = mode == 'copy' data = base64.b64encode(db_file.read()) request.session.proxy("db").restore(restore_pwd, new_db, data, copy) return '' except openerp.exceptions.AccessDenied, e: raise Exception("AccessDenied") @http.route('/web/database/change_password', type='json', auth="none") def change_password(self, fields): old_password, new_password = operator.itemgetter( 'old_pwd', 'new_pwd')( dict(map(operator.itemgetter('name', 'value'), fields))) try: return request.session.proxy("db").change_admin_password(old_password, new_password) except openerp.exceptions.AccessDenied: return {'error': 'AccessDenied', 'title': _('Change Password')} except Exception: return {'error': _('Error, password not changed !'), 'title': _('Change Password')} class Session(http.Controller): def session_info(self): request.session.ensure_valid() return { "session_id": request.session_id, "uid": request.session.uid, "user_context": request.session.get_context() if request.session.uid else {}, "db": request.session.db, "username": request.session.login, } @http.route('/web/session/get_session_info', type='json', auth="none") def get_session_info(self): request.uid = request.session.uid request.disable_db = False return self.session_info() @http.route('/web/session/authenticate', type='json', auth="none") def authenticate(self, db, login, password, base_location=None): request.session.authenticate(db, login, password) return self.session_info() @http.route('/web/session/change_password', type='json', auth="user") def change_password(self, fields): old_password, new_password,confirm_password = operator.itemgetter('old_pwd', 'new_password','confirm_pwd')( dict(map(operator.itemgetter('name', 'value'), fields))) if not (old_password.strip() and new_password.strip() and confirm_password.strip()): return {'error':_('You cannot leave any password empty.'),'title': _('Change Password')} if new_password != confirm_password: return {'error': _('The new password and its confirmation must be identical.'),'title': _('Change Password')} try: if request.session.model('res.users').change_password( old_password, new_password): return {'new_password':new_password} except Exception: return {'error': _('The old password you provided is incorrect, your password was not changed.'), 'title': _('Change Password')} return {'error': _('Error, password not changed !'), 'title': _('Change Password')} @http.route('/web/session/get_lang_list', type='json', auth="none") def get_lang_list(self): try: return request.session.proxy("db").list_lang() or [] except Exception, e: return {"error": e, "title": _("Languages")} @http.route('/web/session/modules', type='json', auth="user") def modules(self): # return all installed modules. Web client is smart enough to not load a module twice return module_installed() @http.route('/web/session/save_session_action', type='json', auth="user") def save_session_action(self, the_action): """ This method store an action object in the session object and returns an integer identifying that action. The method get_session_action() can be used to get back the action. :param the_action: The action to save in the session. :type the_action: anything :return: A key identifying the saved action. :rtype: integer """ return request.httpsession.save_action(the_action) @http.route('/web/session/get_session_action', type='json', auth="user") def get_session_action(self, key): """ Gets back a previously saved action. This method can return None if the action was saved since too much time (this case should be handled in a smart way). :param key: The key given by save_session_action() :type key: integer :return: The saved action or None. :rtype: anything """ return request.httpsession.get_action(key) @http.route('/web/session/check', type='json', auth="user") def check(self): request.session.assert_valid() return None @http.route('/web/session/destroy', type='json', auth="user") def destroy(self): request.session.logout() @http.route('/web/session/logout', type='http', auth="none") def logout(self, redirect='/web'): request.session.logout(keep_db=True) return werkzeug.utils.redirect(redirect, 303) class Menu(http.Controller): @http.route('/web/menu/load_needaction', type='json', auth="user") def load_needaction(self, menu_ids): """ Loads needaction counters for specific menu ids. :return: needaction data :rtype: dict(menu_id: {'needaction_enabled': boolean, 'needaction_counter': int}) """ return request.session.model('ir.ui.menu').get_needaction_data(menu_ids, request.context) class DataSet(http.Controller): @http.route('/web/dataset/search_read', type='json', auth="user") def search_read(self, model, fields=False, offset=0, limit=False, domain=None, sort=None): return self.do_search_read(model, fields, offset, limit, domain, sort) def do_search_read(self, model, fields=False, offset=0, limit=False, domain=None , sort=None): """ Performs a search() followed by a read() (if needed) using the provided search criteria :param str model: the name of the model to search on :param fields: a list of the fields to return in the result records :type fields: [str] :param int offset: from which index should the results start being returned :param int limit: the maximum number of records to return :param list domain: the search domain for the query :param list sort: sorting directives :returns: A structure (dict) with two keys: ids (all the ids matching the (domain, context) pair) and records (paginated records matching fields selection set) :rtype: list """ Model = request.session.model(model) records = Model.search_read(domain, fields, offset or 0, limit or False, sort or False, request.context) if not records: return { 'length': 0, 'records': [] } if limit and len(records) == limit: length = Model.search_count(domain, request.context) else: length = len(records) + (offset or 0) return { 'length': length, 'records': records } @http.route('/web/dataset/load', type='json', auth="user") def load(self, model, id, fields): m = request.session.model(model) value = {} r = m.read([id], False, request.context) if r: value = r[0] return {'value': value} def call_common(self, model, method, args, domain_id=None, context_id=None): return self._call_kw(model, method, args, {}) def _call_kw(self, model, method, args, kwargs): # Temporary implements future display_name special field for model#read() if method in ('read', 'search_read') and kwargs.get('context', {}).get('future_display_name'): if 'display_name' in args[1]: if method == 'read': names = dict(request.session.model(model).name_get(args[0], **kwargs)) else: names = dict(request.session.model(model).name_search('', args[0], **kwargs)) args[1].remove('display_name') records = getattr(request.session.model(model), method)(*args, **kwargs) for record in records: record['display_name'] = \ names.get(record['id']) or "{0}#{1}".format(model, (record['id'])) return records if method.startswith('_'): raise Exception("Access Denied: Underscore prefixed methods cannot be remotely called") return getattr(request.registry.get(model), method)(request.cr, request.uid, *args, **kwargs) @http.route('/web/dataset/call', type='json', auth="user") def call(self, model, method, args, domain_id=None, context_id=None): return self._call_kw(model, method, args, {}) @http.route(['/web/dataset/call_kw', '/web/dataset/call_kw/<path:path>'], type='json', auth="user") def call_kw(self, model, method, args, kwargs, path=None): return self._call_kw(model, method, args, kwargs) @http.route('/web/dataset/call_button', type='json', auth="user") def call_button(self, model, method, args, domain_id=None, context_id=None): action = self._call_kw(model, method, args, {}) if isinstance(action, dict) and action.get('type') != '': return clean_action(action) return False @http.route('/web/dataset/exec_workflow', type='json', auth="user") def exec_workflow(self, model, id, signal): return request.session.exec_workflow(model, id, signal) @http.route('/web/dataset/resequence', type='json', auth="user") def resequence(self, model, ids, field='sequence', offset=0): """ Re-sequences a number of records in the model, by their ids The re-sequencing starts at the first model of ``ids``, the sequence number is incremented by one after each record and starts at ``offset`` :param ids: identifiers of the records to resequence, in the new sequence order :type ids: list(id) :param str field: field used for sequence specification, defaults to "sequence" :param int offset: sequence number for first record in ``ids``, allows starting the resequencing from an arbitrary number, defaults to ``0`` """ m = request.session.model(model) if not m.fields_get([field]): return False # python 2.6 has no start parameter for i, id in enumerate(ids): m.write(id, { field: i + offset }) return True class View(http.Controller): @http.route('/web/view/add_custom', type='json', auth="user") def add_custom(self, view_id, arch): CustomView = request.session.model('ir.ui.view.custom') CustomView.create({ 'user_id': request.session.uid, 'ref_id': view_id, 'arch': arch }, request.context) return {'result': True} @http.route('/web/view/undo_custom', type='json', auth="user") def undo_custom(self, view_id, reset=False): CustomView = request.session.model('ir.ui.view.custom') vcustom = CustomView.search([('user_id', '=', request.session.uid), ('ref_id' ,'=', view_id)], 0, False, False, request.context) if vcustom: if reset: CustomView.unlink(vcustom, request.context) else: CustomView.unlink([vcustom[0]], request.context) return {'result': True} return {'result': False} class TreeView(View): @http.route('/web/treeview/action', type='json', auth="user") def action(self, model, id): return load_actions_from_ir_values( 'action', 'tree_but_open',[(model, id)], False) class Binary(http.Controller): @http.route('/web/binary/image', type='http', auth="public") def image(self, model, id, field, **kw): last_update = '__last_update' Model = request.session.model(model) headers = [('Content-Type', 'image/png')] etag = request.httprequest.headers.get('If-None-Match') hashed_session = hashlib.md5(request.session_id).hexdigest() retag = hashed_session id = None if not id else simplejson.loads(id) if type(id) is list: id = id[0] # m2o try: if etag: if not id and hashed_session == etag: return werkzeug.wrappers.Response(status=304) else: date = Model.read([id], [last_update], request.context)[0].get(last_update) if hashlib.md5(date).hexdigest() == etag: return werkzeug.wrappers.Response(status=304) if not id: res = Model.default_get([field], request.context).get(field) image_base64 = res else: res = Model.read([id], [last_update, field], request.context)[0] retag = hashlib.md5(res.get(last_update)).hexdigest() image_base64 = res.get(field) if kw.get('resize'): resize = kw.get('resize').split(',') if len(resize) == 2 and int(resize[0]) and int(resize[1]): width = int(resize[0]) height = int(resize[1]) # resize maximum 500*500 if width > 500: width = 500 if height > 500: height = 500 image_base64 = openerp.tools.image_resize_image(base64_source=image_base64, size=(width, height), encoding='base64', filetype='PNG') image_data = base64.b64decode(image_base64) except Exception: image_data = self.placeholder() headers.append(('ETag', retag)) headers.append(('Content-Length', len(image_data))) try: ncache = int(kw.get('cache')) headers.append(('Cache-Control', 'no-cache' if ncache == 0 else 'max-age=%s' % (ncache))) except: pass return request.make_response(image_data, headers) def placeholder(self, image='placeholder.png'): addons_path = http.addons_manifest['web']['addons_path'] return open(os.path.join(addons_path, 'web', 'static', 'src', 'img', image), 'rb').read() @http.route('/web/binary/saveas', type='http', auth="public") @serialize_exception def saveas(self, model, field, id=None, filename_field=None, **kw): """ Download link for files stored as binary fields. If the ``id`` parameter is omitted, fetches the default value for the binary field (via ``default_get``), otherwise fetches the field for that precise record. :param str model: name of the model to fetch the binary from :param str field: binary field :param str id: id of the record from which to fetch the binary :param str filename_field: field holding the file's name, if any :returns: :class:`werkzeug.wrappers.Response` """ Model = request.session.model(model) fields = [field] if filename_field: fields.append(filename_field) if id: res = Model.read([int(id)], fields, request.context)[0] else: res = Model.default_get(fields, request.context) filecontent = base64.b64decode(res.get(field, '')) if not filecontent: return request.not_found() else: filename = '%s_%s' % (model.replace('.', '_'), id) if filename_field: filename = res.get(filename_field, '') or filename return request.make_response(filecontent, [('Content-Type', 'application/octet-stream'), ('Content-Disposition', content_disposition(filename))]) @http.route('/web/binary/saveas_ajax', type='http', auth="public") @serialize_exception def saveas_ajax(self, data, token): jdata = simplejson.loads(data) model = jdata['model'] field = jdata['field'] data = jdata['data'] id = jdata.get('id', None) filename_field = jdata.get('filename_field', None) context = jdata.get('context', {}) Model = request.session.model(model) fields = [field] if filename_field: fields.append(filename_field) if data: res = { field: data } elif id: res = Model.read([int(id)], fields, context)[0] else: res = Model.default_get(fields, context) filecontent = base64.b64decode(res.get(field, '')) if not filecontent: raise ValueError(_("No content found for field '%s' on '%s:%s'") % (field, model, id)) else: filename = '%s_%s' % (model.replace('.', '_'), id) if filename_field: filename = res.get(filename_field, '') or filename return request.make_response(filecontent, headers=[('Content-Type', 'application/octet-stream'), ('Content-Disposition', content_disposition(filename))], cookies={'fileToken': token}) @http.route('/web/binary/upload', type='http', auth="user") @serialize_exception def upload(self, callback, ufile): # TODO: might be useful to have a configuration flag for max-length file uploads out = """<script language="javascript" type="text/javascript"> var win = window.top.window; win.jQuery(win).trigger(%s, %s); </script>""" try: data = ufile.read() args = [len(data), ufile.filename, ufile.content_type, base64.b64encode(data)] except Exception, e: args = [False, e.message] return out % (simplejson.dumps(callback), simplejson.dumps(args)) @http.route('/web/binary/upload_attachment', type='http', auth="user") @serialize_exception def upload_attachment(self, callback, model, id, ufile): Model = request.session.model('ir.attachment') out = """<script language="javascript" type="text/javascript"> var win = window.top.window; win.jQuery(win).trigger(%s, %s); </script>""" try: attachment_id = Model.create({ 'name': ufile.filename, 'datas': base64.encodestring(ufile.read()), 'datas_fname': ufile.filename, 'res_model': model, 'res_id': int(id) }, request.context) args = { 'filename': ufile.filename, 'id': attachment_id } except Exception: args = {'error': "Something horrible happened"} return out % (simplejson.dumps(callback), simplejson.dumps(args)) @http.route([ '/web/binary/company_logo', '/logo', '/logo.png', ], type='http', auth="none") def company_logo(self, dbname=None, **kw): imgname = 'logo.png' placeholder = functools.partial(get_module_resource, 'web', 'static', 'src', 'img') uid = None if request.session.db: dbname = request.session.db uid = request.session.uid elif dbname is None: dbname = db_monodb() if not uid: uid = openerp.SUPERUSER_ID if not dbname: response = http.send_file(placeholder(imgname)) else: try: # create an empty registry registry = openerp.modules.registry.Registry(dbname) with registry.cursor() as cr: cr.execute("""SELECT c.logo_web, c.write_date FROM res_users u LEFT JOIN res_company c ON c.id = u.company_id WHERE u.id = %s """, (uid,)) row = cr.fetchone() if row and row[0]: image_data = StringIO(str(row[0]).decode('base64')) response = http.send_file(image_data, filename=imgname, mtime=row[1]) else: response = http.send_file(placeholder('nologo.png')) except Exception: response = http.send_file(placeholder(imgname)) return response class Action(http.Controller): @http.route('/web/action/load', type='json', auth="user") def load(self, action_id, do_not_eval=False, additional_context=None): Actions = request.session.model('ir.actions.actions') value = False try: action_id = int(action_id) except ValueError: try: module, xmlid = action_id.split('.', 1) model, action_id = request.session.model('ir.model.data').get_object_reference(module, xmlid) assert model.startswith('ir.actions.') except Exception: action_id = 0 # force failed read base_action = Actions.read([action_id], ['type'], request.context) if base_action: ctx = request.context action_type = base_action[0]['type'] if action_type == 'ir.actions.report.xml': ctx.update({'bin_size': True}) if additional_context: ctx.update(additional_context) action = request.session.model(action_type).read([action_id], False, ctx) if action: value = clean_action(action[0]) return value @http.route('/web/action/run', type='json', auth="user") def run(self, action_id): return_action = request.session.model('ir.actions.server').run( [action_id], request.context) if return_action: return clean_action(return_action) else: return False class Export(http.Controller): @http.route('/web/export/formats', type='json', auth="user") def formats(self): """ Returns all valid export formats :returns: for each export format, a pair of identifier and printable name :rtype: [(str, str)] """ return [ {'tag': 'csv', 'label': 'CSV'}, {'tag': 'xls', 'label': 'Excel', 'error': None if xlwt else "XLWT required"}, ] def fields_get(self, model): Model = request.session.model(model) fields = Model.fields_get(False, request.context) return fields @http.route('/web/export/get_fields', type='json', auth="user") def get_fields(self, model, prefix='', parent_name= '', import_compat=True, parent_field_type=None, exclude=None): if import_compat and parent_field_type == "many2one": fields = {} else: fields = self.fields_get(model) if import_compat: fields.pop('id', None) else: fields['.id'] = fields.pop('id', {'string': 'ID'}) fields_sequence = sorted(fields.iteritems(), key=lambda field: openerp.tools.ustr(field[1].get('string', ''))) records = [] for field_name, field in fields_sequence: if import_compat: if exclude and field_name in exclude: continue if field.get('readonly'): # If none of the field's states unsets readonly, skip the field if all(dict(attrs).get('readonly', True) for attrs in field.get('states', {}).values()): continue if not field.get('exportable', True): continue id = prefix + (prefix and '/'or '') + field_name name = parent_name + (parent_name and '/' or '') + field['string'] record = {'id': id, 'string': name, 'value': id, 'children': False, 'field_type': field.get('type'), 'required': field.get('required'), 'relation_field': field.get('relation_field')} records.append(record) if len(name.split('/')) < 3 and 'relation' in field: ref = field.pop('relation') record['value'] += '/id' record['params'] = {'model': ref, 'prefix': id, 'name': name} if not import_compat or field['type'] == 'one2many': # m2m field in import_compat is childless record['children'] = True return records @http.route('/web/export/namelist', type='json', auth="user") def namelist(self, model, export_id): # TODO: namelist really has no reason to be in Python (although itertools.groupby helps) export = request.session.model("ir.exports").read([export_id])[0] export_fields_list = request.session.model("ir.exports.line").read( export['export_fields']) fields_data = self.fields_info( model, map(operator.itemgetter('name'), export_fields_list)) return [ {'name': field['name'], 'label': fields_data[field['name']]} for field in export_fields_list ] def fields_info(self, model, export_fields): info = {} fields = self.fields_get(model) if ".id" in export_fields: fields['.id'] = fields.pop('id', {'string': 'ID'}) # To make fields retrieval more efficient, fetch all sub-fields of a # given field at the same time. Because the order in the export list is # arbitrary, this requires ordering all sub-fields of a given field # together so they can be fetched at the same time # # Works the following way: # * sort the list of fields to export, the default sorting order will # put the field itself (if present, for xmlid) and all of its # sub-fields right after it # * then, group on: the first field of the path (which is the same for # a field and for its subfields and the length of splitting on the # first '/', which basically means grouping the field on one side and # all of the subfields on the other. This way, we have the field (for # the xmlid) with length 1, and all of the subfields with the same # base but a length "flag" of 2 # * if we have a normal field (length 1), just add it to the info # mapping (with its string) as-is # * otherwise, recursively call fields_info via graft_subfields. # all graft_subfields does is take the result of fields_info (on the # field's model) and prepend the current base (current field), which # rebuilds the whole sub-tree for the field # # result: because we're not fetching the fields_get for half the # database models, fetching a namelist with a dozen fields (including # relational data) falls from ~6s to ~300ms (on the leads model). # export lists with no sub-fields (e.g. import_compatible lists with # no o2m) are even more efficient (from the same 6s to ~170ms, as # there's a single fields_get to execute) for (base, length), subfields in itertools.groupby( sorted(export_fields), lambda field: (field.split('/', 1)[0], len(field.split('/', 1)))): subfields = list(subfields) if length == 2: # subfields is a seq of $base/*rest, and not loaded yet info.update(self.graft_subfields( fields[base]['relation'], base, fields[base]['string'], subfields )) elif base in fields: info[base] = fields[base]['string'] return info def graft_subfields(self, model, prefix, prefix_string, fields): export_fields = [field.split('/', 1)[1] for field in fields] return ( (prefix + '/' + k, prefix_string + '/' + v) for k, v in self.fields_info(model, export_fields).iteritems()) class ExportFormat(object): raw_data = False @property def content_type(self): """ Provides the format's content type """ raise NotImplementedError() def filename(self, base): """ Creates a valid filename for the format (with extension) from the provided base name (exension-less) """ raise NotImplementedError() def from_data(self, fields, rows): """ Conversion method from OpenERP's export data to whatever the current export class outputs :params list fields: a list of fields to export :params list rows: a list of records to export :returns: :rtype: bytes """ raise NotImplementedError() def base(self, data, token): params = simplejson.loads(data) model, fields, ids, domain, import_compat = \ operator.itemgetter('model', 'fields', 'ids', 'domain', 'import_compat')( params) Model = request.session.model(model) context = dict(request.context or {}, **params.get('context', {})) ids = ids or Model.search(domain, 0, False, False, context) field_names = map(operator.itemgetter('name'), fields) import_data = Model.export_data(ids, field_names, self.raw_data, context=context).get('datas',[]) if import_compat: columns_headers = field_names else: columns_headers = [val['label'].strip() for val in fields] return request.make_response(self.from_data(columns_headers, import_data), headers=[('Content-Disposition', content_disposition(self.filename(model))), ('Content-Type', self.content_type)], cookies={'fileToken': token}) class CSVExport(ExportFormat, http.Controller): @http.route('/web/export/csv', type='http', auth="user") @serialize_exception def index(self, data, token): return self.base(data, token) @property def content_type(self): return 'text/csv;charset=utf8' def filename(self, base): return base + '.csv' def from_data(self, fields, rows): fp = StringIO() writer = csv.writer(fp, quoting=csv.QUOTE_ALL) writer.writerow([name.encode('utf-8') for name in fields]) for data in rows: row = [] for d in data: if isinstance(d, basestring): d = d.replace('\n',' ').replace('\t',' ') try: d = d.encode('utf-8') except UnicodeError: pass if d is False: d = None row.append(d) writer.writerow(row) fp.seek(0) data = fp.read() fp.close() return data class ExcelExport(ExportFormat, http.Controller): # Excel needs raw data to correctly handle numbers and date values raw_data = True @http.route('/web/export/xls', type='http', auth="user") @serialize_exception def index(self, data, token): return self.base(data, token) @property def content_type(self): return 'application/vnd.ms-excel' def filename(self, base): return base + '.xls' def from_data(self, fields, rows): workbook = xlwt.Workbook() worksheet = workbook.add_sheet('Sheet 1') for i, fieldname in enumerate(fields): worksheet.write(0, i, fieldname) worksheet.col(i).width = 8000 # around 220 pixels base_style = xlwt.easyxf('align: wrap yes') date_style = xlwt.easyxf('align: wrap yes', num_format_str='YYYY-MM-DD') datetime_style = xlwt.easyxf('align: wrap yes', num_format_str='YYYY-MM-DD HH:mm:SS') for row_index, row in enumerate(rows): for cell_index, cell_value in enumerate(row): cell_style = base_style if isinstance(cell_value, basestring): cell_value = re.sub("\r", " ", cell_value) elif isinstance(cell_value, datetime.datetime): cell_style = datetime_style elif isinstance(cell_value, datetime.date): cell_style = date_style worksheet.write(row_index + 1, cell_index, cell_value, cell_style) fp = StringIO() workbook.save(fp) fp.seek(0) data = fp.read() fp.close() return data class Reports(http.Controller): POLLING_DELAY = 0.25 TYPES_MAPPING = { 'doc': 'application/vnd.ms-word', 'html': 'text/html', 'odt': 'application/vnd.oasis.opendocument.text', 'pdf': 'application/pdf', 'sxw': 'application/vnd.sun.xml.writer', 'xls': 'application/vnd.ms-excel', } @http.route('/web/report', type='http', auth="user") @serialize_exception def index(self, action, token): action = simplejson.loads(action) report_srv = request.session.proxy("report") context = dict(request.context) context.update(action["context"]) report_data = {} report_ids = context.get("active_ids", None) if 'report_type' in action: report_data['report_type'] = action['report_type'] if 'datas' in action: if 'ids' in action['datas']: report_ids = action['datas'].pop('ids') report_data.update(action['datas']) report_id = report_srv.report( request.session.db, request.session.uid, request.session.password, action["report_name"], report_ids, report_data, context) report_struct = None while True: report_struct = report_srv.report_get( request.session.db, request.session.uid, request.session.password, report_id) if report_struct["state"]: break time.sleep(self.POLLING_DELAY) report = base64.b64decode(report_struct['result']) if report_struct.get('code') == 'zlib': report = zlib.decompress(report) report_mimetype = self.TYPES_MAPPING.get( report_struct['format'], 'octet-stream') file_name = action.get('name', 'report') if 'name' not in action: reports = request.session.model('ir.actions.report.xml') res_id = reports.search([('report_name', '=', action['report_name']),], 0, False, False, context) if len(res_id) > 0: file_name = reports.read(res_id[0], ['name'], context)['name'] else: file_name = action['report_name'] file_name = '%s.%s' % (file_name, report_struct['format']) return request.make_response(report, headers=[ ('Content-Disposition', content_disposition(file_name)), ('Content-Type', report_mimetype), ('Content-Length', len(report))], cookies={'fileToken': token}) class Apps(http.Controller): @http.route('/apps/<app>', auth='user') def get_app_url(self, req, app): act_window_obj = request.session.model('ir.actions.act_window') ir_model_data = request.session.model('ir.model.data') try: action_id = ir_model_data.get_object_reference('base', 'open_module_tree')[1] action = act_window_obj.read(action_id, ['name', 'type', 'res_model', 'view_mode', 'view_type', 'context', 'views', 'domain']) action['target'] = 'current' except ValueError: action = False try: app_id = ir_model_data.get_object_reference('base', 'module_%s' % app)[1] except ValueError: app_id = False if action and app_id: action['res_id'] = app_id action['view_mode'] = 'form' action['views'] = [(False, u'form')] sakey = Session().save_session_action(action) debug = '?debug' if req.debug else '' return werkzeug.utils.redirect('/web{0}#sa={1}'.format(debug, sakey)) # vim:expandtab:tabstop=4:softtabstop=4:shiftwidth=4:
israel-lugo/netcalc
refs/heads/master
netcalc/version.py
1
# NetCalc - advanced network calculator and address planning helper # Copyright (C) 2016, 2017 Israel G. Lugo # # This file is part of NetCalc. # # NetCalc is free software: you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by the # Free Software Foundation, either version 3 of the License, or (at your # option) any later version. # # NetCalc is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # General Public License for more details. # # You should have received a copy of the GNU General Public License along # with NetCalc. If not, see <http://www.gnu.org/licenses/>. # # For suggestions, feedback or bug reports: israel.lugo@lugosys.com """Package version number. Public members: __version__ -- package version number, for internal use """ __version__ = '0.6.2'
simonpatrick/bite-project
refs/heads/master
deps/mrtaskman/server/mapreduce/lib/files/testutil.py
44
#!/usr/bin/env python # # Copyright 2007 Google Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """Testing utils for writing tests involving Files API.""" __all__ = ['TestFileServiceStub'] from google.appengine.api import apiproxy_stub class TestFileServiceStub(apiproxy_stub.APIProxyStub): """A FileServiceStub to be used with tests. Doesn't perform any kind of file validation and stores all file content in memory. Can be used to test low-level file calls only, because it doesn't support all features (like blobstore files). """ def __init__(self): super(TestFileServiceStub, self).__init__('file') self._file_content = {} def _Dynamic_Open(self, request, response): pass def _Dynamic_Close(self, request, response): pass def _Dynamic_Append(self, request, response): self._file_content[request.filename()] = ( self.get_content(request.filename()) + request.data()) def _Dynamic_Read(self, request, response): content = self._file_content[request.filename()] pos = request.pos() response.set_data(content[pos:pos + request.max_bytes()]) def get_content(self, filename): """Get current in-memory file content.""" return self._file_content.get(filename, '') def set_content(self, filename, content): """Set current in-memory file content.""" self._file_content[filename] = content
EricMuller/mywebmarks-backend
refs/heads/master
requirements/twisted/Twisted-17.1.0/docs/core/howto/tutorial/listings/finger/finger/finger.py
2
# finger.py module from zope.interface import Interface, implementer from twisted.application import internet, service, strports from twisted.internet import protocol, reactor, defer, endpoints from twisted.words.protocols import irc from twisted.protocols import basic from twisted.python import components, log from twisted.web import resource, server, xmlrpc from twisted.spread import pb class IFingerService(Interface): def getUser(user): """ Return a deferred returning a string. """ def getUsers(): """ Return a deferred returning a list of strings. """ class IFingerSetterService(Interface): def setUser(user, status): """ Set the user's status to something. """ def catchError(err): return "Internal error in server" class FingerProtocol(basic.LineReceiver): def lineReceived(self, user): d = self.factory.getUser(user) d.addErrback(catchError) def writeValue(value): self.transport.write(value+'\n') self.transport.loseConnection() d.addCallback(writeValue) class IFingerFactory(Interface): def getUser(user): """ Return a deferred returning a string. """ def buildProtocol(addr): """ Return a protocol returning a string. """ @implementer(IFingerFactory) class FingerFactoryFromService(protocol.ServerFactory): protocol = FingerProtocol def __init__(self, service): self.service = service def getUser(self, user): return self.service.getUser(user) components.registerAdapter(FingerFactoryFromService, IFingerService, IFingerFactory) class FingerSetterProtocol(basic.LineReceiver): def connectionMade(self): self.lines = [] def lineReceived(self, line): self.lines.append(line) def connectionLost(self, reason): if len(self.lines) == 2: self.factory.setUser(*self.lines) class IFingerSetterFactory(Interface): def setUser(user, status): """ Return a deferred returning a string. """ def buildProtocol(addr): """ Return a protocol returning a string. """ @implementer(IFingerSetterFactory) class FingerSetterFactoryFromService(protocol.ServerFactory): protocol = FingerSetterProtocol def __init__(self, service): self.service = service def setUser(self, user, status): self.service.setUser(user, status) components.registerAdapter(FingerSetterFactoryFromService, IFingerSetterService, IFingerSetterFactory) class IRCReplyBot(irc.IRCClient): def connectionMade(self): self.nickname = self.factory.nickname irc.IRCClient.connectionMade(self) def privmsg(self, user, channel, msg): user = user.split('!')[0] if self.nickname.lower() == channel.lower(): d = self.factory.getUser(msg) d.addErrback(catchError) d.addCallback(lambda m: "Status of %s: %s" % (msg, m)) d.addCallback(lambda m: self.msg(user, m)) class IIRCClientFactory(Interface): """ @ivar nickname """ def getUser(user): """ Return a deferred returning a string. """ def buildProtocol(addr): """ Return a protocol. """ @implementer(IIRCClientFactory) class IRCClientFactoryFromService(protocol.ClientFactory): protocol = IRCReplyBot nickname = None def __init__(self, service): self.service = service def getUser(self, user): return self.service.getUser(user) components.registerAdapter(IRCClientFactoryFromService, IFingerService, IIRCClientFactory) class UserStatusTree(resource.Resource): template = """<html><head><title>Users</title></head><body> <h1>Users</h1> <ul> %(users)s </ul> </body> </html>""" def __init__(self, service): resource.Resource.__init__(self) self.service = service def getChild(self, path, request): if path == '': return self elif path == 'RPC2': return UserStatusXR(self.service) else: return UserStatus(path, self.service) def render_GET(self, request): users = self.service.getUsers() def cbUsers(users): request.write(self.template % {'users': ''.join([ # Name should be quoted properly these uses. '<li><a href="%s">%s</a></li>' % (name, name) for name in users])}) request.finish() users.addCallback(cbUsers) def ebUsers(err): log.err(err, "UserStatusTree failed") request.finish() users.addErrback(ebUsers) return server.NOT_DONE_YET components.registerAdapter(UserStatusTree, IFingerService, resource.IResource) class UserStatus(resource.Resource): template='''<html><head><title>%(title)s</title></head> <body><h1>%(name)s</h1><p>%(status)s</p></body></html>''' def __init__(self, user, service): resource.Resource.__init__(self) self.user = user self.service = service def render_GET(self, request): status = self.service.getUser(self.user) def cbStatus(status): request.write(self.template % { 'title': self.user, 'name': self.user, 'status': status}) request.finish() status.addCallback(cbStatus) def ebStatus(err): log.err(err, "UserStatus failed") request.finish() status.addErrback(ebStatus) return server.NOT_DONE_YET class UserStatusXR(xmlrpc.XMLRPC): def __init__(self, service): xmlrpc.XMLRPC.__init__(self) self.service = service def xmlrpc_getUser(self, user): return self.service.getUser(user) def xmlrpc_getUsers(self): return self.service.getUsers() class IPerspectiveFinger(Interface): def remote_getUser(username): """ Return a user's status. """ def remote_getUsers(): """ Return a user's status. """ @implementer(IPerspectiveFinger) class PerspectiveFingerFromService(pb.Root): def __init__(self, service): self.service = service def remote_getUser(self, username): return self.service.getUser(username) def remote_getUsers(self): return self.service.getUsers() components.registerAdapter(PerspectiveFingerFromService, IFingerService, IPerspectiveFinger) @implementer(IFingerService) class FingerService(service.Service): def __init__(self, filename): self.filename = filename def _read(self): self.users = {} with open(self.filename) as f: for line in f: user, status = line.split(':', 1) user = user.strip() status = status.strip() self.users[user] = status self.call = reactor.callLater(30, self._read) def getUser(self, user): return defer.succeed(self.users.get(user, "No such user")) def getUsers(self): return defer.succeed(self.users.keys()) def startService(self): self._read() service.Service.startService(self) def stopService(self): service.Service.stopService(self) self.call.cancel() # Easy configuration def makeService(config): # finger on port 79 s = service.MultiService() f = FingerService(config['file']) h = strports.service("tcp:1079", IFingerFactory(f)) h.setServiceParent(s) # website on port 8000 r = resource.IResource(f) r.templateDirectory = config['templates'] site = server.Site(r) j = strports.service("tcp:8000", site) j.setServiceParent(s) # ssl on port 443 # if config.get('ssl'): # k = strports.service( # "ssl:port=443:certKey=cert.pem:privateKey=key.pem", site # ) # k.setServiceParent(s) # irc fingerbot if 'ircnick' in config: i = IIRCClientFactory(f) i.nickname = config['ircnick'] ircserver = config['ircserver'] b = internet.ClientService( endpoints.HostnameEndpoint(reactor, ircserver, 6667), i ) b.setServiceParent(s) # Pespective Broker on port 8889 if 'pbport' in config: m = internet.StreamServerEndpointService( endpoints.TCP4ServerEndpoint(reactor, int(config['pbport'])), pb.PBServerFactory(IPerspectiveFinger(f)) ) m.setServiceParent(s) return s
yorvic/.vim
refs/heads/master
bundle/python-mode/pylibs/pylama/checkers/pylint/logilab/astng/utils.py
1
# copyright 2003-2013 LOGILAB S.A. (Paris, FRANCE), all rights reserved. # contact http://www.logilab.fr/ -- mailto:contact@logilab.fr # # This file is part of logilab-astng. # # logilab-astng is free software: you can redistribute it and/or modify it # under the terms of the GNU Lesser General Public License as published by the # Free Software Foundation, either version 2.1 of the License, or (at your # option) any later version. # # logilab-astng is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License # for more details. # # You should have received a copy of the GNU Lesser General Public License along # with logilab-astng. If not, see <http://www.gnu.org/licenses/>. """this module contains some utilities to navigate in the tree or to extract information from it """ __docformat__ = "restructuredtext en" from .exceptions import ASTNGBuildingException from .builder import parse class ASTWalker: """a walker visiting a tree in preorder, calling on the handler: * visit_<class name> on entering a node, where class name is the class of the node in lower case * leave_<class name> on leaving a node, where class name is the class of the node in lower case """ def __init__(self, handler): self.handler = handler self._cache = {} def walk(self, node, _done=None): """walk on the tree from <node>, getting callbacks from handler""" if _done is None: _done = set() if node in _done: raise AssertionError((id(node), node, node.parent)) _done.add(node) self.visit(node) for child_node in node.get_children(): self.handler.set_context(node, child_node) assert child_node is not node self.walk(child_node, _done) self.leave(node) assert node.parent is not node def get_callbacks(self, node): """get callbacks from handler for the visited node""" klass = node.__class__ methods = self._cache.get(klass) if methods is None: handler = self.handler kid = klass.__name__.lower() e_method = getattr(handler, 'visit_%s' % kid, getattr(handler, 'visit_default', None)) l_method = getattr(handler, 'leave_%s' % kid, getattr(handler, 'leave_default', None)) self._cache[klass] = (e_method, l_method) else: e_method, l_method = methods return e_method, l_method def visit(self, node): """walk on the tree from <node>, getting callbacks from handler""" method = self.get_callbacks(node)[0] if method is not None: method(node) def leave(self, node): """walk on the tree from <node>, getting callbacks from handler""" method = self.get_callbacks(node)[1] if method is not None: method(node) class LocalsVisitor(ASTWalker): """visit a project by traversing the locals dictionary""" def __init__(self): ASTWalker.__init__(self, self) self._visited = {} def visit(self, node): """launch the visit starting from the given node""" if node in self._visited: return self._visited[node] = 1 # FIXME: use set ? methods = self.get_callbacks(node) if methods[0] is not None: methods[0](node) if 'locals' in node.__dict__: # skip Instance and other proxy for name, local_node in node.items(): self.visit(local_node) if methods[1] is not None: return methods[1](node) def _check_children(node): """a helper function to check children - parent relations""" for child in node.get_children(): ok = False if child is None: print "Hm, child of %s is None" % node continue if not hasattr(child, 'parent'): print " ERROR: %s has child %s %x with no parent" % (node, child, id(child)) elif not child.parent: print " ERROR: %s has child %s %x with parent %r" % (node, child, id(child), child.parent) elif child.parent is not node: print " ERROR: %s %x has child %s %x with wrong parent %s" % (node, id(node), child, id(child), child.parent) else: ok = True if not ok: print "lines;", node.lineno, child.lineno print "of module", node.root(), node.root().name raise ASTNGBuildingException _check_children(child) class TreeTester(object): '''A helper class to see _ast tree and compare with astng tree indent: string for tree indent representation lineno: bool to tell if we should print the line numbers >>> tester = TreeTester('print') >>> print tester.native_tree_repr() <Module> . body = [ . <Print> . . nl = True . ] >>> print tester.astng_tree_repr() Module() body = [ Print() dest = values = [ ] ] ''' indent = '. ' lineno = False def __init__(self, sourcecode): self._string = '' self.sourcecode = sourcecode self._ast_node = None self.build_ast() def build_ast(self): """build the _ast tree from the source code""" self._ast_node = parse(self.sourcecode) def native_tree_repr(self, node=None, indent=''): """get a nice representation of the _ast tree""" self._string = '' if node is None: node = self._ast_node self._native_repr_tree(node, indent) return self._string def _native_repr_tree(self, node, indent, _done=None): """recursive method for the native tree representation""" from _ast import Load as _Load, Store as _Store, Del as _Del from _ast import AST as Node if _done is None: _done = set() if node in _done: self._string += '\nloop in tree: %r (%s)' % (node, getattr(node, 'lineno', None)) return _done.add(node) self._string += '\n' + indent + '<%s>' % node.__class__.__name__ indent += self.indent if not hasattr(node, '__dict__'): self._string += '\n' + self.indent + " ** node has no __dict__ " + str(node) return node_dict = node.__dict__ if hasattr(node, '_attributes'): for a in node._attributes: attr = node_dict[a] if attr is None: continue if a in ("lineno", "col_offset") and not self.lineno: continue self._string +='\n' + indent + a + " = " + repr(attr) for field in node._fields or (): attr = node_dict[field] if attr is None: continue if isinstance(attr, list): if not attr: continue self._string += '\n' + indent + field + ' = [' for elt in attr: self._native_repr_tree(elt, indent, _done) self._string += '\n' + indent + ']' continue if isinstance(attr, (_Load, _Store, _Del)): continue if isinstance(attr, Node): self._string += '\n' + indent + field + " = " self._native_repr_tree(attr, indent, _done) else: self._string += '\n' + indent + field + " = " + repr(attr) def build_astng_tree(self): """build astng tree from the _ast tree """ from logilab.astng.builder import ASTNGBuilder tree = ASTNGBuilder().string_build(self.sourcecode) return tree def astng_tree_repr(self, ids=False): """build the astng tree and return a nice tree representation""" mod = self.build_astng_tree() return mod.repr_tree(ids) __all__ = ('LocalsVisitor', 'ASTWalker',)
bolmez/Class-HARK
refs/heads/master
HARKutilities.py
2
''' General purpose / miscellaneous functions. Includes functions to approximate continuous distributions with discrete ones, utility functions (and their derivatives), manipulation of discrete distributions, and basic plotting tools. ''' from __future__ import division # Import Python 3.x division function import functools import re # Regular expression, for string cleaning import warnings import numpy as np # Python's numeric library, abbreviated "np" import pylab as plt # Python's plotting library import scipy.stats as stats # Python's statistics library from scipy.interpolate import interp1d from scipy.special import erf def _warning(message,category = UserWarning,filename = '',lineno = -1): ''' A "monkeypatch" to warnings, to print pretty-looking warnings. The default behavior of the "warnings" module is to print some extra, unusual- looking things when the user calls a warning. A common "fix" for this is to "monkeypatch" the warnings module. See: http://stackoverflow.com/questions/2187269/python-print-only-the-message-on-warnings I implement this fix directly below, for all simulation and solution utilities. ''' print(message) warnings.showwarning = _warning def memoize(obj): ''' A decorator to (potentially) make functions more efficient. With this decorator, functions will "remember" if they have been evaluated with given inputs before. If they have, they will "remember" the outputs that have already been calculated for those inputs, rather than calculating them again. ''' cache = obj._cache = {} @functools.wraps(obj) def memoizer(*args, **kwargs): key = str(args) + str(kwargs) if key not in cache: cache[key] = obj(*args, **kwargs) return cache[key] return memoizer # ============================================================================== # ============== Some basic function tools ==================================== # ============================================================================== def getArgNames(function): ''' Returns a list of strings naming all of the arguments for the passed function. Parameters ---------- function : function A function whose argument names are wanted. Returns ------- argNames : [string] The names of the arguments of function. ''' argCount = function.__code__.co_argcount argNames = function.__code__.co_varnames[:argCount] return argNames class NullFunc(): ''' A trivial class that acts as a placeholder "do nothing" function. ''' def __call__(self,*args): ''' Returns meaningless output no matter what the input(s) is. If no input, returns None. Otherwise, returns an array of NaNs (or a single NaN) of the same size as the first input. ''' if len(args) == 0: return None else: arg = args[0] if hasattr(arg,'shape'): return np.zeros_like(arg) + np.nan else: return np.nan def distance(self,other): ''' Trivial distance metric that only cares whether the other object is also an instance of NullFunc. Intentionally does not inherit from HARKobject as this might create dependency problems. Parameters ---------- other : any Any object for comparison to this instance of NullFunc. Returns ------- (unnamed) : float The distance between self and other. Returns 0 if other is also a NullFunc; otherwise returns an arbitrary high number. ''' try: if other.__class__ is self.__class__: return 0.0 else: return 1000.0 except: return 10000.0 # ============================================================================== # ============== Define utility functions =============================== # ============================================================================== def CRRAutility(c, gam): ''' Evaluates constant relative risk aversion (CRRA) utility of consumption c given risk aversion parameter gam. Parameters ---------- c : float Consumption value gam : float Risk aversion Returns ------- (unnamed) : float Utility Tests ----- Test a value which should pass: >>> c, gamma = 1.0, 2.0 # Set two values at once with Python syntax >>> utility(c=c, gam=gamma) -1.0 ''' if gam == 1: return np.log(c) else: return( c**(1.0 - gam) / (1.0 - gam) ) def CRRAutilityP(c, gam): ''' Evaluates constant relative risk aversion (CRRA) marginal utility of consumption c given risk aversion parameter gam. Parameters ---------- c : float Consumption value gam : float Risk aversion Returns ------- (unnamed) : float Marginal utility ''' return( c**-gam ) def CRRAutilityPP(c, gam): ''' Evaluates constant relative risk aversion (CRRA) marginal marginal utility of consumption c given risk aversion parameter gam. Parameters ---------- c : float Consumption value gam : float Risk aversion Returns ------- (unnamed) : float Marginal marginal utility ''' return( -gam*c**(-gam-1.0) ) def CRRAutilityPPP(c, gam): ''' Evaluates constant relative risk aversion (CRRA) marginal marginal marginal utility of consumption c given risk aversion parameter gam. Parameters ---------- c : float Consumption value gam : float Risk aversion Returns ------- (unnamed) : float Marginal marginal marginal utility ''' return( (gam+1.0)*gam*c**(-gam-2.0) ) def CRRAutilityPPPP(c, gam): ''' Evaluates constant relative risk aversion (CRRA) marginal marginal marginal marginal utility of consumption c given risk aversion parameter gam. Parameters ---------- c : float Consumption value gam : float Risk aversion Returns ------- (unnamed) : float Marginal marginal marginal marginal utility ''' return( -(gam+2.0)*(gam+1.0)*gam*c**(-gam-3.0) ) def CRRAutility_inv(u, gam): ''' Evaluates the inverse of the CRRA utility function (with risk aversion para- meter gam) at a given utility level u. Parameters ---------- u : float Utility value gam : float Risk aversion Returns ------- (unnamed) : float Consumption corresponding to given utility value ''' if gam == 1: return np.exp(u) else: return( ((1.0-gam)*u)**(1/(1.0-gam)) ) def CRRAutilityP_inv(uP, gam): ''' Evaluates the inverse of the CRRA marginal utility function (with risk aversion parameter gam) at a given marginal utility level uP. Parameters ---------- uP : float Marginal utility value gam : float Risk aversion Returns ------- (unnamed) : float Consumption corresponding to given marginal utility value. ''' return( uP**(-1.0/gam) ) def CRRAutility_invP(u, gam): ''' Evaluates the derivative of the inverse of the CRRA utility function (with risk aversion parameter gam) at a given utility level u. Parameters ---------- u : float Utility value gam : float Risk aversion Returns ------- (unnamed) : float Marginal consumption corresponding to given utility value ''' if gam == 1: return np.exp(u) else: return( ((1.0-gam)*u)**(gam/(1.0-gam)) ) def CRRAutilityP_invP(u, gam): ''' Evaluates the derivative of the inverse of the CRRA marginal utility function (with risk aversion parameter gam) at a given marginal utility level uP. Parameters ---------- uP : float Marginal utility value gam : float Risk aversion Returns ------- (unnamed) : float Marginal consumption corresponding to given marginal utility value ''' return( (-1.0/gam)*u**(-1.0/gam-1.0) ) def CARAutility(c, alpha): ''' Evaluates constant absolute risk aversion (CARA) utility of consumption c given risk aversion parameter alpha. Parameters ---------- c: float Consumption value alpha: float Risk aversion Returns ------- (unnamed): float Utility ''' return( 1 - np.exp(-alpha*c)/alpha ) def CARAutilityP(c, alpha): ''' Evaluates constant absolute risk aversion (CARA) marginal utility of consumption c given risk aversion parameter alpha. Parameters ---------- c: float Consumption value alpha: float Risk aversion Returns ------- (unnamed): float Marginal utility ''' return( np.exp(-alpha*c) ) def CARAutilityPP(c, alpha): ''' Evaluates constant absolute risk aversion (CARA) marginal marginal utility of consumption c given risk aversion parameter alpha. Parameters ---------- c: float Consumption value alpha: float Risk aversion Returns ------- (unnamed): float Marginal marginal utility ''' return( -alpha*np.exp(-alpha*c) ) def CARAutilityPPP(c, alpha): ''' Evaluates constant absolute risk aversion (CARA) marginal marginal marginal utility of consumption c given risk aversion parameter alpha. Parameters ---------- c: float Consumption value alpha: float Risk aversion Returns ------- (unnamed): float Marginal marginal marginal utility ''' return( alpha**2.0*np.exp(-alpha*c) ) def CARAutility_inv(u, alpha): ''' Evaluates inverse of constant absolute risk aversion (CARA) utility function at utility level u given risk aversion parameter alpha. Parameters ---------- u: float Utility value alpha: float Risk aversion Returns ------- (unnamed): float Consumption value corresponding to u ''' return( -1.0/alpha * np.log(alpha*(1-u)) ) def CARAutilityP_inv(u, alpha): ''' Evaluates the inverse of constant absolute risk aversion (CARA) marginal utility function at marginal utility uP given risk aversion parameter alpha. Parameters ---------- u: float Utility value alpha: float Risk aversion Returns ------- (unnamed): float Consumption value corresponding to uP ''' return( -1.0/alpha*np.log(u) ) def CARAutility_invP(u, alpha): ''' Evaluates the derivative of inverse of constant absolute risk aversion (CARA) utility function at utility level u given risk aversion parameter alpha. Parameters ---------- u: float Utility value alpha: float Risk aversion Returns ------- (unnamed): float Marginal onsumption value corresponding to u ''' return( 1.0/(alpha*(1.0-u)) ) def approxLognormal(N, mu=0.0, sigma=1.0, tail_N=0, tail_bound=[0.02,0.98], tail_order=np.e): ''' Construct a discrete approximation to a lognormal distribution with underlying normal distribution N(exp(mu),sigma). Makes an equiprobable distribution by default, but user can optionally request augmented tails with exponentially sized point masses. This can improve solution accuracy in some models. Parameters ---------- N: int Number of discrete points in the "main part" of the approximation. mu: float Mean of underlying normal distribution. sigma: float Standard deviation of underlying normal distribution. tail_N: int Number of points in each "tail part" of the approximation; 0 = no tail. tail_bound: [float] CDF boundaries of the tails vs main portion; tail_bound[0] is the lower tail bound, tail_bound[1] is the upper tail bound. Inoperative when tail_N = 0. Can make "one tailed" approximations with 0.0 or 1.0. tail_order: float Factor by which consecutive point masses in a "tail part" differ in probability. Should be >= 1 for sensible spacing. Returns ------- pmf: np.ndarray Probabilities for discrete probability mass function. X: np.ndarray Discrete values in probability mass function. Written by Luca Gerotto Based on Matab function "setup_workspace.m," from Chris Carroll's [Solution Methods for Microeconomic Dynamic Optimization Problems] (http://www.econ2.jhu.edu/people/ccarroll/solvingmicrodsops/) toolkit. Latest update: 21 April 2016 by Matthew N. White ''' # Find the CDF boundaries of each segment if sigma > 0.0: if tail_N > 0: lo_cut = tail_bound[0] hi_cut = tail_bound[1] else: lo_cut = 0.0 hi_cut = 1.0 inner_size = hi_cut - lo_cut inner_CDF_vals = [lo_cut + x*N**(-1.0)*inner_size for x in range(1, N)] if inner_size < 1.0: scale = 1.0/tail_order mag = (1.0-scale**tail_N)/(1.0-scale) lower_CDF_vals = [0.0] if lo_cut > 0.0: for x in range(tail_N-1,-1,-1): lower_CDF_vals.append(lower_CDF_vals[-1] + lo_cut*scale**x/mag) upper_CDF_vals = [hi_cut] if hi_cut < 1.0: for x in range(tail_N): upper_CDF_vals.append(upper_CDF_vals[-1] + (1.0-hi_cut)*scale**x/mag) CDF_vals = lower_CDF_vals + inner_CDF_vals + upper_CDF_vals temp_cutoffs = list(stats.lognorm.ppf(CDF_vals[1:-1], s=sigma, loc=0, scale=np.exp(mu))) cutoffs = [0] + temp_cutoffs + [np.inf] CDF_vals = np.array(CDF_vals) # Construct the discrete approximation by finding the average value within each segment K = CDF_vals.size-1 # number of points in approximation pmf = CDF_vals[1:(K+1)] - CDF_vals[0:K] X = np.zeros(K) for i in range(K): zBot = cutoffs[i] zTop = cutoffs[i+1] X[i] = (-0.5)*np.exp(mu+(sigma**2)*0.5)*(erf((mu+sigma**2-np.log(zTop))*( (np.sqrt(2)*sigma)**(-1)))-erf((mu+sigma**2-np.log(zBot))*((np.sqrt(2)*sigma) **(-1))))*(pmf[i]**(-1)) else: pmf = np.ones(N)/N X = np.exp(mu)*np.ones(N) return [pmf, X] @memoize def approxMeanOneLognormal(N, sigma=1.0, **kwargs): ''' Calculate a discrete approximation to a mean one lognormal distribution. Based on function approxLognormal; see that function's documentation for further notes. Parameters ---------- N : int Size of discrete space vector to be returned. sigma : float standard deviation associated with underlying normal probability distribution. Returns ------- X : np.array Discrete points for discrete probability mass function. pmf : np.array Probability associated with each point in X. Written by Nathan M. Palmer Based on Matab function "setup_shocks.m," from Chris Carroll's [Solution Methods for Microeconomic Dynamic Optimization Problems] (http://www.econ2.jhu.edu/people/ccarroll/solvingmicrodsops/) toolkit. Latest update: 01 May 2015 ''' mu_adj = - 0.5*sigma**2; pmf,X = approxLognormal(N=N, mu=mu_adj, sigma=sigma, **kwargs) return [pmf,X] def approxBeta(N,a=1.0,b=1.0): ''' Calculate a discrete approximation to the beta distribution. May be quite slow, as it uses a rudimentary numeric integration method to generate the discrete approximation. Parameters ---------- N : int Size of discrete space vector to be returned. a : float First shape parameter (sometimes called alpha). b : float Second shape parameter (sometimes called beta). Returns ------- X : np.array Discrete points for discrete probability mass function. pmf : np.array Probability associated with each point in X. ''' P = 1000 vals = np.reshape(stats.beta.ppf(np.linspace(0.0,1.0,N*P),a,b),(N,P)) X = np.mean(vals,axis=1) pmf = np.ones(N)/float(N) return( [pmf, X] ) def approxUniform(N,bot=0.0,top=1.0): ''' Makes a discrete approximation to a uniform distribution, given its bottom and top limits and number of points. Parameters ---------- N : int The number of points in the discrete approximation bot : float The bottom of the uniform distribution top : float The top of the uniform distribution Returns ------- (unnamed) : np.array An equiprobable discrete approximation to the uniform distribution. ''' pmf = np.ones(N)/float(N) center = (top+bot)/2.0 width = (top-bot)/2.0 X = center + width*np.linspace(-(N-1.0)/2.0,(N-1.0)/2.0,N)/(N/2.0) return [pmf,X] def makeMarkovApproxToNormal(x_grid,mu,sigma,K=351,bound=3.5): ''' Creates an approximation to a normal distribution with mean mu and standard deviation sigma, returning a stochastic vector called p_vec, corresponding to values in x_grid. If a RV is distributed x~N(mu,sigma), then the expectation of a continuous function f() is E[f(x)] = numpy.dot(p_vec,f(x_grid)). Parameters ---------- x_grid: numpy.array A sorted 1D array of floats representing discrete values that a normally distributed RV could take on. mu: float Mean of the normal distribution to be approximated. sigma: float Standard deviation of the normal distribution to be approximated. K: int Number of points in the normal distribution to sample. bound: float Truncation bound of the normal distribution, as +/- bound*sigma. Returns ------- p_vec: numpy.array A stochastic vector with probability weights for each x in x_grid. ''' x_n = x_grid.size # Number of points in the outcome grid lower_bound = -bound # Lower bound of normal draws to consider, in SD upper_bound = bound # Upper bound of normal draws to consider, in SD raw_sample = np.linspace(lower_bound,upper_bound,K) # Evenly spaced draws between bounds f_weights = stats.norm.pdf(raw_sample) # Relative probability of each draw sample = mu + sigma*raw_sample # Adjusted bounds, given mean and stdev w_vec = np.zeros(x_n) # A vector of outcome weights # Find the relative position of each of the draws sample_pos = np.searchsorted(x_grid,sample) sample_pos[sample_pos < 1] = 1 sample_pos[sample_pos > x_n-1] = x_n-1 # Make arrays of the x_grid point directly above and below each draw bot = x_grid[sample_pos-1] top = x_grid[sample_pos] alpha = (sample-bot)/(top-bot) # Loop through each x_grid point and add up the probability that each nearby # draw contributes to it (accounting for distance) for j in range(1,x_n): c = sample_pos == j w_vec[j-1] = w_vec[j-1] + np.dot(f_weights[c],1.0-alpha[c]) w_vec[j] = w_vec[j] + np.dot(f_weights[c],alpha[c]) # Reweight the probabilities so they sum to 1, and return W = np.sum(w_vec) p_vec = w_vec/W return p_vec # ================================================================================ # ==================== Functions for manipulating discrete distributions ========= # ================================================================================ def addDiscreteOutcomeConstantMean(distribution, x, p, sort = False): ''' Adds a discrete outcome of x with probability p to an existing distribution, holding constant the relative probabilities of other outcomes and overall mean. Parameters ---------- distribution : [np.array] Two element list containing a list of probabilities and a list of outcomes. x : float The new value to be added to the distribution. p : float The probability of the discrete outcome x occuring. sort: bool Whether or not to sort X before returning it Returns ------- X : np.array Discrete points for discrete probability mass function. pmf : np.array Probability associated with each point in X. Written by Matthew N. White Latest update: 08 December 2015 by David Low ''' X = np.append(x,distribution[1]*(1-p*x)/(1-p)) pmf = np.append(p,distribution[0]*(1-p)) if sort: indices = np.argsort(X) X = X[indices] pmf = pmf[indices] return([pmf,X]) def addDiscreteOutcome(distribution, x, p, sort = False): ''' Adds a discrete outcome of x with probability p to an existing distribution, holding constant the relative probabilities of other outcomes. Parameters ---------- distribution : [np.array] Two element list containing a list of probabilities and a list of outcomes. x : float The new value to be added to the distribution. p : float The probability of the discrete outcome x occuring. Returns ------- X : np.array Discrete points for discrete probability mass function. pmf : np.array Probability associated with each point in X. Written by Matthew N. White Latest update: 11 December 2015 ''' X = np.append(x,distribution[1]) pmf = np.append(p,distribution[0]*(1-p)) if sort: indices = np.argsort(X) X = X[indices] pmf = pmf[indices] return([pmf,X]) def combineIndepDstns(*distributions): ''' Given n lists (or tuples) whose elements represent n independent, discrete probability spaces (probabilities and values), construct a joint pmf over all combinations of these independent points. Parameters ---------- distributions : [np.array] Arbitrary number of distributions (pmfs). Each pmf is a list or tuple. For each pmf, the first vector is probabilities and the second is values. For each pmf, this should be true: len(X_pmf[0]) = len(X_pmf[1]) Returns ------- List of arrays, consisting of: P_out: np.array Probability associated with each point in X_out. X_out: np.array (as many as in *distributions) Discrete points for the joint discrete probability mass function. Written by Nathan Palmer Latest update: 31 August 2015 by David Low ''' # Very quick and incomplete parameter check: for dist in distributions: assert len(dist[0]) == len(dist[-1]), "len(dist[0]) != len(dist[-1])" # Get information on the distributions dist_lengths = () for dist in distributions: dist_lengths += (len(dist[0]),) number_of_distributions = len(distributions) # Initialize lists we will use X_out = [] P_temp = [] # Now loop through the distributions, tiling and flattening as necessary. for dd,dist in enumerate(distributions): # The shape we want before we tile dist_newshape = (1,) * dd + (len(dist[0]),) + \ (1,) * (number_of_distributions - dd) # The tiling we want to do dist_tiles = dist_lengths[:dd] + (1,) + dist_lengths[dd+1:] # Now we are ready to tile. # We don't use the np.meshgrid commands, because they do not # easily support non-symmetric grids. Xmesh = np.tile(dist[1].reshape(dist_newshape),dist_tiles) Pmesh = np.tile(dist[0].reshape(dist_newshape),dist_tiles) # Now flatten the tiled arrays. flatX = Xmesh.ravel() flatP = Pmesh.ravel() # Add the flattened arrays to the output lists. X_out += [flatX,] P_temp += [flatP,] # We're done getting the flattened X_out arrays we wanted. # However, we have a bunch of flattened P_temp arrays, and just want one # probability array. So get the probability array, P_out, here. P_out = np.ones_like(X_out[0]) for pp in P_temp: P_out *= pp assert np.isclose(np.sum(P_out),1),'Probabilities do not sum to 1!' return [P_out,] + X_out # ============================================================================== # ============== Functions for generating state space grids =================== # ============================================================================== def makeGridExpMult(ming, maxg, ng, timestonest=20): ''' Make a multi-exponentially spaced grid. Parameters ---------- ming : float Minimum value of the grid maxg : float Maximum value of the grid ng : int The number of grid points timestonest : int the number of times to nest the exponentiation Returns ------- points : np.array A multi-exponentially spaced grid Original Matab code can be found in Chris Carroll's [Solution Methods for Microeconomic Dynamic Optimization Problems] (http://www.econ2.jhu.edu/people/ccarroll/solvingmicrodsops/) toolkit. Latest update: 01 May 2015 ''' if timestonest > 0: Lming = ming Lmaxg = maxg for j in range(timestonest): Lming = np.log(Lming + 1) Lmaxg = np.log(Lmaxg + 1) Lgrid = np.linspace(Lming,Lmaxg,ng) grid = Lgrid for j in range(timestonest): grid = np.exp(grid) - 1 else: Lming = np.log(ming) Lmaxg = np.log(maxg) Lstep = (Lmaxg - Lming)/(ng - 1) Lgrid = np.arange(Lming,Lmaxg+0.000001,Lstep) grid = np.exp(Lgrid) return(grid) # ============================================================================== # ============== Uncategorized general functions =================== # ============================================================================== def calcWeightedAvg(data,weights): ''' Generates a weighted average of simulated data. The Nth row of data is averaged and then weighted by the Nth element of weights in an aggregate average. Parameters ---------- data : numpy.array An array of data with N rows of J floats weights : numpy.array A length N array of weights for the N rows of data. Returns ------- weighted_sum : float The weighted sum of the data. ''' data_avg = np.mean(data,axis=1) weighted_sum = np.dot(data_avg,weights) return weighted_sum def getPercentiles(data,weights=None,percentiles=[0.5],presorted=False): ''' Calculates the requested percentiles of (weighted) data. Median by default. Parameters ---------- data : numpy.array A 1D array of float data. weights : np.array A weighting vector for the data. percentiles : [float] A list of percentiles to calculate for the data. Each element should be in (0,1). presorted : boolean Indicator for whether data has already been sorted. Returns ------- pctl_out : numpy.array The requested percentiles of the data. ''' if weights is None: # Set equiprobable weights if none were passed weights = np.ones(data.size)/float(data.size) if presorted: # Sort the data if it is not already data_sorted = data weights_sorted = weights else: order = np.argsort(data) data_sorted = data[order] weights_sorted = weights[order] cum_dist = np.cumsum(weights_sorted)/np.sum(weights_sorted) # cumulative probability distribution # Calculate the requested percentiles by interpolating the data over the # cumulative distribution, then evaluating at the percentile values inv_CDF = interp1d(cum_dist,data_sorted,bounds_error=False,assume_sorted=True) pctl_out = inv_CDF(percentiles) return pctl_out def getLorenzShares(data,weights=None,percentiles=[0.5],presorted=False): ''' Calculates the Lorenz curve at the requested percentiles of (weighted) data. Median by default. Parameters ---------- data : numpy.array A 1D array of float data. weights : numpy.array A weighting vector for the data. percentiles : [float] A list of percentiles to calculate for the data. Each element should be in (0,1). presorted : boolean Indicator for whether data has already been sorted. Returns ------- lorenz_out : numpy.array The requested Lorenz curve points of the data. ''' if weights is None: # Set equiprobable weights if none were given weights = np.ones(data.size) if presorted: # Sort the data if it is not already data_sorted = data weights_sorted = weights else: order = np.argsort(data) data_sorted = data[order] weights_sorted = weights[order] cum_dist = np.cumsum(weights_sorted)/np.sum(weights_sorted) # cumulative probability distribution temp = data_sorted*weights_sorted cum_data = np.cumsum(temp)/sum(temp) # cumulative ownership shares # Calculate the requested Lorenz shares by interpolating the cumulative ownership # shares over the cumulative distribution, then evaluating at requested points lorenzFunc = interp1d(cum_dist,cum_data,bounds_error=False,assume_sorted=True) lorenz_out = lorenzFunc(percentiles) return lorenz_out def calcSubpopAvg(data,reference,cutoffs,weights=None): ''' Calculates the average of (weighted) data between cutoff percentiles of a reference variable. Parameters ---------- data : numpy.array A 1D array of float data. reference : numpy.array A 1D array of float data of the same length as data. cutoffs : [(float,float)] A list of doubles with the lower and upper percentile bounds (should be in [0,1]). weights : numpy.array A weighting vector for the data. Returns ------- slice_avg The (weighted) average of data that falls within the cutoff percentiles of reference. ''' if weights is None: # Set equiprobable weights if none were given weights = np.ones(data.size) # Sort the data and generate a cumulative distribution order = np.argsort(reference) data_sorted = data[order] weights_sorted = weights[order] cum_dist = np.cumsum(weights_sorted)/np.sum(weights_sorted) # For each set of cutoffs, calculate the average of data that falls within # the cutoff percentiles of reference slice_avg = [] for j in range(len(cutoffs)): bot = np.searchsorted(cum_dist,cutoffs[j][0]) top = np.searchsorted(cum_dist,cutoffs[j][1]) slice_avg.append(np.sum(data_sorted[bot:top]*weights_sorted[bot:top])/ np.sum(weights_sorted[bot:top])) return slice_avg def kernelRegression(x,y,bot=None,top=None,N=500,h=None): ''' Performs a non-parametric Nadaraya-Watson 1D kernel regression on given data with optionally specified range, number of points, and kernel bandwidth. Parameters ---------- x : np.array The independent variable in the kernel regression. y : np.array The dependent variable in the kernel regression. bot : float Minimum value of interest in the regression; defaults to min(x). top : float Maximum value of interest in the regression; defaults to max(y). N : int Number of points to compute. h : float The bandwidth of the (Epanechnikov) kernel. To-do: GENERALIZE. Returns ------- regression : LinearInterp A piecewise locally linear kernel regression: y = f(x). ''' # Fix omitted inputs if bot is None: bot = np.min(x) if top is None: top = np.max(x) if h is None: h = 2.0*(top - bot)/float(N) # This is an arbitrary default # Construct a local linear approximation x_vec = np.linspace(bot,top,num=N) y_vec = np.zeros_like(x_vec) + np.nan for j in range(N): x_here = x_vec[j] weights = epanechnikovKernel(x,x_here,h) y_vec[j] = np.dot(weights,y)/np.sum(weights) regression = interp1d(x_vec,y_vec,bounds_error=False,assume_sorted=True) return regression def epanechnikovKernel(x,ref_x,h=1.0): ''' The Epanechnikov kernel. Parameters ---------- x : np.array Values at which to evaluate the kernel x_ref : float The reference point h : float Kernel bandwidth Returns ------- out : np.array Kernel values at each value of x ''' u = (x-ref_x)/h # Normalize distance by bandwidth these = np.abs(u) <= 1.0 # Kernel = 0 outside [-1,1] out = np.zeros_like(x) # Initialize kernel output out[these] = 0.75*(1.0-u[these]**2.0) # Evaluate kernel return out # ============================================================================== # ============== Some basic plotting tools ==================================== # ============================================================================== def plotFuncs(functions,bottom,top,N=1000,legend_kwds = None): ''' Plots 1D function(s) over a given range. Parameters ---------- functions : [function] or function A single function, or a list of functions, to be plotted. bottom : float The lower limit of the domain to be plotted. top : float The upper limit of the domain to be plotted. N : int Number of points in the domain to evaluate. legend_kwds: None, or dictionary If not None, the keyword dictionary to pass to plt.legend Returns ------- none ''' if type(functions)==list: function_list = functions else: function_list = [functions] step = (top-bottom)/N for function in function_list: x = np.arange(bottom,top,step) y = function(x) plt.plot(x,y) plt.xlim([bottom, top]) if legend_kwds is not None: plt.legend(**legend_kwds) plt.show() def plotFuncsDer(functions,bottom,top,N=1000,legend_kwds = None): ''' Plots the first derivative of 1D function(s) over a given range. Parameters ---------- function : function A function or list of functions, the derivatives of which are to be plotted. bottom : float The lower limit of the domain to be plotted. top : float The upper limit of the domain to be plotted. N : int Number of points in the domain to evaluate. legend_kwds: None, or dictionary If not None, the keyword dictionary to pass to plt.legend Returns ------- none ''' if type(functions)==list: function_list = functions else: function_list = [functions] step = (top-bottom)/N for function in function_list: x = np.arange(bottom,top,step) y = function.derivative(x) plt.plot(x,y) plt.xlim([bottom, top]) if legend_kwds is not None: plt.legend(**legend_kwds) plt.show() if __name__ == '__main__': print("Sorry, HARKutilities doesn't actually do anything on its own.") print("To see some examples of its functions in action, look at any") print("of the model modules in /ConsumptionSavingModel. As these functions") print("are the basic building blocks of HARK, you'll find them used") print("everywhere! In the future, this module will show examples of each") print("function in the module.")
zofuthan/edx-platform
refs/heads/master
common/djangoapps/enrollment/data.py
39
""" Data Aggregation Layer of the Enrollment API. Collects all enrollment specific data into a single source to be used throughout the API. """ import logging from django.contrib.auth.models import User from opaque_keys.edx.keys import CourseKey from enrollment.errors import ( CourseNotFoundError, CourseEnrollmentClosedError, CourseEnrollmentFullError, CourseEnrollmentExistsError, UserNotFoundError, InvalidEnrollmentAttribute ) from enrollment.serializers import CourseEnrollmentSerializer, CourseField from openedx.core.djangoapps.content.course_overviews.models import CourseOverview from student.models import ( CourseEnrollment, NonExistentCourseError, EnrollmentClosedError, CourseFullError, AlreadyEnrolledError, CourseEnrollmentAttribute ) log = logging.getLogger(__name__) def get_course_enrollments(user_id): """Retrieve a list representing all aggregated data for a user's course enrollments. Construct a representation of all course enrollment data for a specific user. Args: user_id (str): The name of the user to retrieve course enrollment information for. Returns: A serializable list of dictionaries of all aggregated enrollment data for a user. """ qset = CourseEnrollment.objects.filter( user__username=user_id, is_active=True ).order_by('created') return CourseEnrollmentSerializer(qset).data def get_course_enrollment(username, course_id): """Retrieve an object representing all aggregated data for a user's course enrollment. Get the course enrollment information for a specific user and course. Args: username (str): The name of the user to retrieve course enrollment information for. course_id (str): The course to retrieve course enrollment information for. Returns: A serializable dictionary representing the course enrollment. """ course_key = CourseKey.from_string(course_id) try: enrollment = CourseEnrollment.objects.get( user__username=username, course_id=course_key ) return CourseEnrollmentSerializer(enrollment).data except CourseEnrollment.DoesNotExist: return None def create_course_enrollment(username, course_id, mode, is_active): """Create a new course enrollment for the given user. Creates a new course enrollment for the specified user username. Args: username (str): The name of the user to create a new course enrollment for. course_id (str): The course to create the course enrollment for. mode (str): (Optional) The mode for the new enrollment. is_active (boolean): (Optional) Determines if the enrollment is active. Returns: A serializable dictionary representing the new course enrollment. Raises: CourseNotFoundError CourseEnrollmentFullError EnrollmentClosedError CourseEnrollmentExistsError """ course_key = CourseKey.from_string(course_id) try: user = User.objects.get(username=username) except User.DoesNotExist: msg = u"Not user with username '{username}' found.".format(username=username) log.warn(msg) raise UserNotFoundError(msg) try: enrollment = CourseEnrollment.enroll(user, course_key, check_access=True) return _update_enrollment(enrollment, is_active=is_active, mode=mode) except NonExistentCourseError as err: raise CourseNotFoundError(err.message) except EnrollmentClosedError as err: raise CourseEnrollmentClosedError(err.message) except CourseFullError as err: raise CourseEnrollmentFullError(err.message) except AlreadyEnrolledError as err: enrollment = get_course_enrollment(username, course_id) raise CourseEnrollmentExistsError(err.message, enrollment) def update_course_enrollment(username, course_id, mode=None, is_active=None): """Modify a course enrollment for a user. Allows updates to a specific course enrollment. Args: username (str): The name of the user to retrieve course enrollment information for. course_id (str): The course to retrieve course enrollment information for. mode (str): (Optional) If specified, modify the mode for this enrollment. is_active (boolean): (Optional) Determines if the enrollment is active. Returns: A serializable dictionary representing the modified course enrollment. """ course_key = CourseKey.from_string(course_id) try: user = User.objects.get(username=username) except User.DoesNotExist: msg = u"Not user with username '{username}' found.".format(username=username) log.warn(msg) raise UserNotFoundError(msg) try: enrollment = CourseEnrollment.objects.get(user=user, course_id=course_key) return _update_enrollment(enrollment, is_active=is_active, mode=mode) except CourseEnrollment.DoesNotExist: return None def add_or_update_enrollment_attr(user_id, course_id, attributes): """Set enrollment attributes for the enrollment of given user in the course provided. Args: course_id (str): The Course to set enrollment attributes for. user_id (str): The User to set enrollment attributes for. attributes (list): Attributes to be set. Example: >>>add_or_update_enrollment_attr( "Bob", "course-v1-edX-DemoX-1T2015", [ { "namespace": "credit", "name": "provider_id", "value": "hogwarts", }, ] ) """ course_key = CourseKey.from_string(course_id) user = _get_user(user_id) enrollment = CourseEnrollment.get_enrollment(user, course_key) if not _invalid_attribute(attributes) and enrollment is not None: CourseEnrollmentAttribute.add_enrollment_attr(enrollment, attributes) def get_enrollment_attributes(user_id, course_id): """Retrieve enrollment attributes for given user for provided course. Args: user_id: The User to get enrollment attributes for course_id (str): The Course to get enrollment attributes for. Example: >>>get_enrollment_attributes("Bob", "course-v1-edX-DemoX-1T2015") [ { "namespace": "credit", "name": "provider_id", "value": "hogwarts", }, ] Returns: list """ course_key = CourseKey.from_string(course_id) user = _get_user(user_id) enrollment = CourseEnrollment.get_enrollment(user, course_key) return CourseEnrollmentAttribute.get_enrollment_attributes(enrollment) def _get_user(user_id): """Retrieve user with provided user_id Args: user_id(str): username of the user for which object is to retrieve Returns: obj """ try: return User.objects.get(username=user_id) except User.DoesNotExist: msg = u"Not user with username '{username}' found.".format(username=user_id) log.warn(msg) raise UserNotFoundError(msg) def _update_enrollment(enrollment, is_active=None, mode=None): enrollment.update_enrollment(is_active=is_active, mode=mode) enrollment.save() return CourseEnrollmentSerializer(enrollment).data def _invalid_attribute(attributes): """Validate enrollment attribute Args: attributes(dict): dict of attribute Return: list of invalid attributes """ invalid_attributes = [] for attribute in attributes: if "namespace" not in attribute: msg = u"'namespace' not in enrollment attribute" log.warn(msg) invalid_attributes.append("namespace") raise InvalidEnrollmentAttribute(msg) if "name" not in attribute: msg = u"'name' not in enrollment attribute" log.warn(msg) invalid_attributes.append("name") raise InvalidEnrollmentAttribute(msg) if "value" not in attribute: msg = u"'value' not in enrollment attribute" log.warn(msg) invalid_attributes.append("value") raise InvalidEnrollmentAttribute(msg) return invalid_attributes def get_course_enrollment_info(course_id, include_expired=False): """Returns all course enrollment information for the given course. Based on the course id, return all related course information. Args: course_id (str): The course to retrieve enrollment information for. include_expired (bool): Boolean denoting whether expired course modes should be included in the returned JSON data. Returns: A serializable dictionary representing the course's enrollment information. Raises: CourseNotFoundError """ course_key = CourseKey.from_string(course_id) try: course = CourseOverview.get_from_id(course_key) except CourseOverview.DoesNotExist: msg = u"Requested enrollment information for unknown course {course}".format(course=course_id) log.warning(msg) raise CourseNotFoundError(msg) else: return CourseField().to_native(course, include_expired=include_expired)
levenlabs/ansible
refs/heads/stable-2.1
lib/ansible/utils/module_docs_fragments/azure_tags.py
16
#!/usr/bin/python # # Copyright (c) 2016 Matt Davis, <mdavis@ansible.com> # Chris Houseknecht, <house@redhat.com> # # This file is part of Ansible # # Ansible is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # Ansible is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Ansible. If not, see <http://www.gnu.org/licenses/>. # class ModuleDocFragment(object): # Azure doc fragment DOCUMENTATION = ''' options: tags: description: - "Dictionary of string:string pairs to assign as metadata to the object. Metadata tags on the object will be updated with any provided values. To remove tags set append_tags option to false." required: false default: null append_tags: description: - Use to control if tags field is cannonical or just appends to existing tags. When cannonical, any tags not found in the tags parameter will be removed from the object's metadata. default: True required: false '''
kronicz/ecommerce-2
refs/heads/master
lib/python2.7/site-packages/django/contrib/gis/db/models/lookups.py
84
from __future__ import unicode_literals import re from django.core.exceptions import FieldDoesNotExist from django.db.models.constants import LOOKUP_SEP from django.db.models.expressions import Col, Expression from django.db.models.lookups import Lookup from django.utils import six gis_lookups = {} class GISLookup(Lookup): sql_template = None transform_func = None distance = False @classmethod def _check_geo_field(cls, opts, lookup): """ Utility for checking the given lookup with the given model options. The lookup is a string either specifying the geographic field, e.g. 'point, 'the_geom', or a related lookup on a geographic field like 'address__point'. If a GeometryField exists according to the given lookup on the model options, it will be returned. Otherwise returns None. """ from django.contrib.gis.db.models.fields import GeometryField # This takes into account the situation where the lookup is a # lookup to a related geographic field, e.g., 'address__point'. field_list = lookup.split(LOOKUP_SEP) # Reversing so list operates like a queue of related lookups, # and popping the top lookup. field_list.reverse() fld_name = field_list.pop() try: geo_fld = opts.get_field(fld_name) # If the field list is still around, then it means that the # lookup was for a geometry field across a relationship -- # thus we keep on getting the related model options and the # model field associated with the next field in the list # until there's no more left. while len(field_list): opts = geo_fld.rel.to._meta geo_fld = opts.get_field(field_list.pop()) except (FieldDoesNotExist, AttributeError): return False # Finally, make sure we got a Geographic field and return. if isinstance(geo_fld, GeometryField): return geo_fld else: return False def get_db_prep_lookup(self, value, connection): # get_db_prep_lookup is called by process_rhs from super class if isinstance(value, (tuple, list)): # First param is assumed to be the geometric object params = [connection.ops.Adapter(value[0])] + list(value)[1:] else: params = [connection.ops.Adapter(value)] return ('%s', params) def process_rhs(self, compiler, connection): rhs, rhs_params = super(GISLookup, self).process_rhs(compiler, connection) if hasattr(self.rhs, '_as_sql'): # If rhs is some QuerySet, don't touch it return rhs, rhs_params geom = self.rhs if isinstance(self.rhs, Col): # Make sure the F Expression destination field exists, and # set an `srid` attribute with the same as that of the # destination. geo_fld = self.rhs.output_field if not hasattr(geo_fld, 'srid'): raise ValueError('No geographic field found in expression.') self.rhs.srid = geo_fld.srid elif isinstance(self.rhs, Expression): raise ValueError('Complex expressions not supported for GeometryField') elif isinstance(self.rhs, (list, tuple)): geom = self.rhs[0] rhs = connection.ops.get_geom_placeholder(self.lhs.output_field, geom, compiler) return rhs, rhs_params def as_sql(self, compiler, connection): lhs_sql, sql_params = self.process_lhs(compiler, connection) rhs_sql, rhs_params = self.process_rhs(compiler, connection) sql_params.extend(rhs_params) template_params = {'lhs': lhs_sql, 'rhs': rhs_sql} backend_op = connection.ops.gis_operators[self.lookup_name] return backend_op.as_sql(connection, self, template_params, sql_params) # ------------------ # Geometry operators # ------------------ class OverlapsLeftLookup(GISLookup): """ The overlaps_left operator returns true if A's bounding box overlaps or is to the left of B's bounding box. """ lookup_name = 'overlaps_left' gis_lookups['overlaps_left'] = OverlapsLeftLookup class OverlapsRightLookup(GISLookup): """ The 'overlaps_right' operator returns true if A's bounding box overlaps or is to the right of B's bounding box. """ lookup_name = 'overlaps_right' gis_lookups['overlaps_right'] = OverlapsRightLookup class OverlapsBelowLookup(GISLookup): """ The 'overlaps_below' operator returns true if A's bounding box overlaps or is below B's bounding box. """ lookup_name = 'overlaps_below' gis_lookups['overlaps_below'] = OverlapsBelowLookup class OverlapsAboveLookup(GISLookup): """ The 'overlaps_above' operator returns true if A's bounding box overlaps or is above B's bounding box. """ lookup_name = 'overlaps_above' gis_lookups['overlaps_above'] = OverlapsAboveLookup class LeftLookup(GISLookup): """ The 'left' operator returns true if A's bounding box is strictly to the left of B's bounding box. """ lookup_name = 'left' gis_lookups['left'] = LeftLookup class RightLookup(GISLookup): """ The 'right' operator returns true if A's bounding box is strictly to the right of B's bounding box. """ lookup_name = 'right' gis_lookups['right'] = RightLookup class StrictlyBelowLookup(GISLookup): """ The 'strictly_below' operator returns true if A's bounding box is strictly below B's bounding box. """ lookup_name = 'strictly_below' gis_lookups['strictly_below'] = StrictlyBelowLookup class StrictlyAboveLookup(GISLookup): """ The 'strictly_above' operator returns true if A's bounding box is strictly above B's bounding box. """ lookup_name = 'strictly_above' gis_lookups['strictly_above'] = StrictlyAboveLookup class SameAsLookup(GISLookup): """ The "~=" operator is the "same as" operator. It tests actual geometric equality of two features. So if A and B are the same feature, vertex-by-vertex, the operator returns true. """ lookup_name = 'same_as' gis_lookups['same_as'] = SameAsLookup class ExactLookup(SameAsLookup): # Alias of same_as lookup_name = 'exact' gis_lookups['exact'] = ExactLookup class BBContainsLookup(GISLookup): """ The 'bbcontains' operator returns true if A's bounding box completely contains by B's bounding box. """ lookup_name = 'bbcontains' gis_lookups['bbcontains'] = BBContainsLookup class BBOverlapsLookup(GISLookup): """ The 'bboverlaps' operator returns true if A's bounding box overlaps B's bounding box. """ lookup_name = 'bboverlaps' gis_lookups['bboverlaps'] = BBOverlapsLookup class ContainedLookup(GISLookup): """ The 'contained' operator returns true if A's bounding box is completely contained by B's bounding box. """ lookup_name = 'contained' gis_lookups['contained'] = ContainedLookup # ------------------ # Geometry functions # ------------------ class ContainsLookup(GISLookup): lookup_name = 'contains' gis_lookups['contains'] = ContainsLookup class ContainsProperlyLookup(GISLookup): lookup_name = 'contains_properly' gis_lookups['contains_properly'] = ContainsProperlyLookup class CoveredByLookup(GISLookup): lookup_name = 'coveredby' gis_lookups['coveredby'] = CoveredByLookup class CoversLookup(GISLookup): lookup_name = 'covers' gis_lookups['covers'] = CoversLookup class CrossesLookup(GISLookup): lookup_name = 'crosses' gis_lookups['crosses'] = CrossesLookup class DisjointLookup(GISLookup): lookup_name = 'disjoint' gis_lookups['disjoint'] = DisjointLookup class EqualsLookup(GISLookup): lookup_name = 'equals' gis_lookups['equals'] = EqualsLookup class IntersectsLookup(GISLookup): lookup_name = 'intersects' gis_lookups['intersects'] = IntersectsLookup class OverlapsLookup(GISLookup): lookup_name = 'overlaps' gis_lookups['overlaps'] = OverlapsLookup class RelateLookup(GISLookup): lookup_name = 'relate' sql_template = '%(func)s(%(lhs)s, %(rhs)s, %%s)' pattern_regex = re.compile(r'^[012TF\*]{9}$') def get_db_prep_lookup(self, value, connection): if len(value) != 2: raise ValueError('relate must be passed a two-tuple') # Check the pattern argument backend_op = connection.ops.gis_operators[self.lookup_name] if hasattr(backend_op, 'check_relate_argument'): backend_op.check_relate_argument(value[1]) else: pattern = value[1] if not isinstance(pattern, six.string_types) or not self.pattern_regex.match(pattern): raise ValueError('Invalid intersection matrix pattern "%s".' % pattern) return super(RelateLookup, self).get_db_prep_lookup(value, connection) gis_lookups['relate'] = RelateLookup class TouchesLookup(GISLookup): lookup_name = 'touches' gis_lookups['touches'] = TouchesLookup class WithinLookup(GISLookup): lookup_name = 'within' gis_lookups['within'] = WithinLookup class DistanceLookupBase(GISLookup): distance = True sql_template = '%(func)s(%(lhs)s, %(rhs)s) %(op)s %%s' def get_db_prep_lookup(self, value, connection): if isinstance(value, (tuple, list)): if not 2 <= len(value) <= 3: raise ValueError("2 or 3-element tuple required for '%s' lookup." % self.lookup_name) params = [connection.ops.Adapter(value[0])] # Getting the distance parameter in the units of the field. params += connection.ops.get_distance(self.lhs.output_field, value[1:], self.lookup_name) return ('%s', params) else: return super(DistanceLookupBase, self).get_db_prep_lookup(value, connection) class DWithinLookup(DistanceLookupBase): lookup_name = 'dwithin' sql_template = '%(func)s(%(lhs)s, %(rhs)s, %%s)' gis_lookups['dwithin'] = DWithinLookup class DistanceGTLookup(DistanceLookupBase): lookup_name = 'distance_gt' gis_lookups['distance_gt'] = DistanceGTLookup class DistanceGTELookup(DistanceLookupBase): lookup_name = 'distance_gte' gis_lookups['distance_gte'] = DistanceGTELookup class DistanceLTLookup(DistanceLookupBase): lookup_name = 'distance_lt' gis_lookups['distance_lt'] = DistanceLTLookup class DistanceLTELookup(DistanceLookupBase): lookup_name = 'distance_lte' gis_lookups['distance_lte'] = DistanceLTELookup
indictranstech/reciphergroup-erpnext
refs/heads/master
erpnext/accounts/doctype/journal_entry/journal_entry.py
4
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors # License: GNU General Public License v3. See license.txt from __future__ import unicode_literals import frappe from frappe.utils import cstr, flt, fmt_money, formatdate, getdate, date_diff from frappe import msgprint, _, scrub from erpnext.setup.utils import get_company_currency from erpnext.controllers.accounts_controller import AccountsController from erpnext.accounts.utils import get_balance_on class JournalEntry(AccountsController): def __init__(self, arg1, arg2=None): super(JournalEntry, self).__init__(arg1, arg2) def get_feed(self): return self.voucher_type def validate(self): if not self.is_opening: self.is_opening='No' self.clearance_date = None super(JournalEntry, self).validate_date_with_fiscal_year() self.validate_party() self.validate_cheque_info() self.validate_entries_for_advance() self.validate_debit_and_credit() self.validate_against_jv() self.validate_reference_doc() self.set_against_account() self.create_remarks() self.set_print_format_fields() self.validate_expense_claim() self.validate_credit_debit_note() self.validate_empty_accounts_table() self.set_title() def on_submit(self): self.check_credit_limit() self.make_gl_entries() self.update_advance_paid() self.update_expense_claim() def set_title(self): self.title = self.pay_to_recd_from or self.accounts[0].account def update_advance_paid(self): advance_paid = frappe._dict() for d in self.get("accounts"): if d.is_advance: if d.reference_type in ("Sales Order", "Purchase Order"): advance_paid.setdefault(d.reference_type, []).append(d.reference_name) for voucher_type, order_list in advance_paid.items(): for voucher_no in list(set(order_list)): frappe.get_doc(voucher_type, voucher_no).set_total_advance_paid() def on_cancel(self): from erpnext.accounts.utils import remove_against_link_from_jv remove_against_link_from_jv(self.doctype, self.name) self.make_gl_entries(1) self.update_advance_paid() self.update_expense_claim() def validate_party(self): for d in self.get("accounts"): account_type = frappe.db.get_value("Account", d.account, "account_type") if account_type in ["Receivable", "Payable"]: if not (d.party_type and d.party): frappe.throw(_("Row {0}: Party Type and Party is required for Receivable / Payable account {1}").format(d.idx, d.account)) elif d.party_type and d.party: frappe.throw(_("Row {0}: Party Type and Party is only applicable against Receivable / Payable account").format(d.idx)) def check_credit_limit(self): customers = list(set([d.party for d in self.get("accounts") if d.party_type=="Customer" and d.party and flt(d.debit) > 0])) if customers: from erpnext.selling.doctype.customer.customer import check_credit_limit for customer in customers: check_credit_limit(customer, self.company) def validate_cheque_info(self): if self.voucher_type in ['Bank Entry']: if not self.cheque_no or not self.cheque_date: msgprint(_("Reference No & Reference Date is required for {0}").format(self.voucher_type), raise_exception=1) if self.cheque_date and not self.cheque_no: msgprint(_("Reference No is mandatory if you entered Reference Date"), raise_exception=1) def validate_entries_for_advance(self): for d in self.get('accounts'): if d.reference_type not in ("Sales Invoice", "Purchase Invoice", "Journal Entry"): if (d.party_type == 'Customer' and flt(d.credit) > 0) or \ (d.party_type == 'Supplier' and flt(d.debit) > 0): if d.is_advance=="No": msgprint(_("Row {0}: Please check 'Is Advance' against Account {1} if this is an advance entry.").format(d.idx, d.account)) elif d.reference_type in ("Sales Order", "Purchase Order") and d.is_advance != "Yes": frappe.throw(_("Row {0}: Payment against Sales/Purchase Order should always be marked as advance").format(d.idx)) def validate_against_jv(self): for d in self.get('accounts'): if d.reference_type=="Journal Entry": account_root_type = frappe.db.get_value("Account", d.account, "root_type") if account_root_type == "Asset" and flt(d.debit) > 0: frappe.throw(_("For {0}, only credit accounts can be linked against another debit entry") .format(d.account)) elif account_root_type == "Liability" and flt(d.credit) > 0: frappe.throw(_("For {0}, only debit accounts can be linked against another credit entry") .format(d.account)) if d.reference_name == self.name: frappe.throw(_("You can not enter current voucher in 'Against Journal Entry' column")) against_entries = frappe.db.sql("""select * from `tabJournal Entry Account` where account = %s and docstatus = 1 and parent = %s and ifnull(reference_type, '') in ("", "Sales Order", "Purchase Order") """, (d.account, d.reference_name), as_dict=True) if not against_entries: frappe.throw(_("Journal Entry {0} does not have account {1} or already matched against other voucher") .format(d.reference_name, d.account)) else: dr_or_cr = "debit" if d.credit > 0 else "credit" valid = False for jvd in against_entries: if flt(jvd[dr_or_cr]) > 0: valid = True if not valid: frappe.throw(_("Against Journal Entry {0} does not have any unmatched {1} entry") .format(d.reference_name, dr_or_cr)) def validate_reference_doc(self): """Validates reference document""" field_dict = { 'Sales Invoice': ["Customer", "Debit To"], 'Purchase Invoice': ["Supplier", "Credit To"], 'Sales Order': ["Customer"], 'Purchase Order': ["Supplier"] } self.reference_totals = {} self.reference_types = {} for d in self.get("accounts"): if not d.reference_type: d.reference_name = None if not d.reference_name: d.reference_type = None if d.reference_type and d.reference_name and (d.reference_type in field_dict.keys()): dr_or_cr = "credit" if d.reference_type in ("Sales Order", "Sales Invoice") \ else "debit" # check debit or credit type Sales / Purchase Order if d.reference_type=="Sales Order" and flt(d.debit) > 0: frappe.throw(_("Row {0}: Debit entry can not be linked with a {1}").format(d.idx, d.reference_type)) if d.reference_type == "Purchase Order" and flt(d.credit) > 0: frappe.throw(_("Row {0}: Credit entry can not be linked with a {1}").format(d.idx, d.reference_type)) # set totals if not d.reference_name in self.reference_totals: self.reference_totals[d.reference_name] = 0.0 self.reference_totals[d.reference_name] += flt(d.get(dr_or_cr)) self.reference_types[d.reference_name] = d.reference_type against_voucher = frappe.db.get_value(d.reference_type, d.reference_name, [scrub(dt) for dt in field_dict.get(d.reference_type)]) # check if party and account match if d.reference_type in ("Sales Invoice", "Purchase Invoice"): if (against_voucher[0] != d.party or against_voucher[1] != d.account): frappe.throw(_("Row {0}: Party / Account does not match with {1} / {2} in {3} {4}") .format(d.idx, field_dict.get(d.reference_type)[0], field_dict.get(d.reference_type)[1], d.reference_type, d.reference_name)) # check if party matches for Sales / Purchase Order if d.reference_type in ("Sales Order", "Purchase Order"): # set totals if against_voucher != d.party: frappe.throw(_("Row {0}: {1} {2} does not match with {3}") \ .format(d.idx, d.party_type, d.party, d.reference_type)) self.validate_orders() self.validate_invoices() def validate_orders(self): """Validate totals, stopped and docstatus for orders""" for reference_name, total in self.reference_totals.iteritems(): reference_type = self.reference_types[reference_name] if reference_type in ("Sales Order", "Purchase Order"): voucher_properties = frappe.db.get_value(reference_type, reference_name, ["docstatus", "per_billed", "status", "advance_paid", "base_grand_total"]) if voucher_properties[0] != 1: frappe.throw(_("{0} {1} is not submitted").format(reference_type, reference_name)) if flt(voucher_properties[1]) >= 100: frappe.throw(_("{0} {1} is fully billed").format(reference_type, reference_name)) if cstr(voucher_properties[2]) == "Stopped": frappe.throw(_("{0} {1} is stopped").format(reference_type, reference_name)) if flt(voucher_properties[4]) < (flt(voucher_properties[3]) + total): frappe.throw(_("Advance paid against {0} {1} cannot be greater \ than Grand Total {2}").format(reference_type, reference_name, voucher_properties[4])) def validate_invoices(self): """Validate totals and docstatus for invoices""" for reference_name, total in self.reference_totals.iteritems(): reference_type = self.reference_types[reference_name] if reference_type in ("Sales Invoice", "Purchase Invoice"): voucher_properties = frappe.db.get_value(reference_type, reference_name, ["docstatus", "outstanding_amount"]) if voucher_properties[0] != 1: frappe.throw(_("{0} {1} is not submitted").format(reference_type, reference_name)) if total and flt(voucher_properties[1]) < total: frappe.throw(_("Payment against {0} {1} cannot be greater \ than Outstanding Amount {2}").format(reference_type, reference_name, voucher_properties[1])) def set_against_account(self): accounts_debited, accounts_credited = [], [] for d in self.get("accounts"): if flt(d.debit > 0): accounts_debited.append(d.party or d.account) if flt(d.credit) > 0: accounts_credited.append(d.party or d.account) for d in self.get("accounts"): if flt(d.debit > 0): d.against_account = ", ".join(list(set(accounts_credited))) if flt(d.credit > 0): d.against_account = ", ".join(list(set(accounts_debited))) def validate_debit_and_credit(self): self.total_debit, self.total_credit, self.difference = 0, 0, 0 for d in self.get("accounts"): if d.debit and d.credit: frappe.throw(_("You cannot credit and debit same account at the same time")) self.total_debit = flt(self.total_debit) + flt(d.debit, self.precision("debit", "accounts")) self.total_credit = flt(self.total_credit) + flt(d.credit, self.precision("credit", "accounts")) self.difference = flt(self.total_debit, self.precision("total_debit")) - \ flt(self.total_credit, self.precision("total_credit")) if self.difference: frappe.throw(_("Total Debit must be equal to Total Credit. The difference is {0}") .format(self.difference)) def create_remarks(self): r = [] if self.cheque_no: if self.cheque_date: r.append(_('Reference #{0} dated {1}').format(self.cheque_no, formatdate(self.cheque_date))) else: msgprint(_("Please enter Reference date"), raise_exception=frappe.MandatoryError) company_currency = get_company_currency(self.company) for d in self.get('accounts'): if d.reference_type=="Sales Invoice" and d.credit: r.append(_("{0} against Sales Invoice {1}").format(fmt_money(flt(d.credit), currency = company_currency), \ d.reference_name)) if d.reference_type=="Sales Order" and d.credit: r.append(_("{0} against Sales Order {1}").format(fmt_money(flt(d.credit), currency = company_currency), \ d.reference_name)) if d.reference_type == "Purchase Invoice" and d.debit: bill_no = frappe.db.sql("""select bill_no, bill_date from `tabPurchase Invoice` where name=%s""", d.reference_name) if bill_no and bill_no[0][0] and bill_no[0][0].lower().strip() \ not in ['na', 'not applicable', 'none']: r.append(_('{0} against Bill {1} dated {2}').format(fmt_money(flt(d.debit), currency=company_currency), bill_no[0][0], bill_no[0][1] and formatdate(bill_no[0][1].strftime('%Y-%m-%d')))) if d.reference_type == "Purchase Order" and d.debit: r.append(_("{0} against Purchase Order {1}").format(fmt_money(flt(d.credit), currency = company_currency), \ d.reference_name)) if self.user_remark: r.append(_("Note: {0}").format(self.user_remark)) if r: self.remark = ("\n").join(r) #User Remarks is not mandatory def set_print_format_fields(self): for d in self.get('accounts'): if d.party_type and d.party: if not self.pay_to_recd_from: self.pay_to_recd_from = frappe.db.get_value(d.party_type, d.party, "customer_name" if d.party_type=="Customer" else "supplier_name") self.set_total_amount(d.debit or d.credit) elif frappe.db.get_value("Account", d.account, "account_type") in ["Bank", "Cash"]: self.set_total_amount(d.debit or d.credit) def set_total_amount(self, amt): company_currency = get_company_currency(self.company) self.total_amount = amt from frappe.utils import money_in_words self.total_amount_in_words = money_in_words(amt, company_currency) def make_gl_entries(self, cancel=0, adv_adj=0): from erpnext.accounts.general_ledger import make_gl_entries gl_map = [] for d in self.get("accounts"): if d.debit or d.credit: gl_map.append( self.get_gl_dict({ "account": d.account, "party_type": d.party_type, "party": d.party, "against": d.against_account, "debit": flt(d.debit, self.precision("debit", "accounts")), "credit": flt(d.credit, self.precision("credit", "accounts")), "against_voucher_type": d.reference_type, "against_voucher": d.reference_name, "remarks": self.remark, "cost_center": d.cost_center }) ) if gl_map: make_gl_entries(gl_map, cancel=cancel, adv_adj=adv_adj) def get_balance(self): if not self.get('accounts'): msgprint(_("'Entries' cannot be empty"), raise_exception=True) else: flag, self.total_debit, self.total_credit = 0, 0, 0 diff = flt(self.difference, self.precision("difference")) # If any row without amount, set the diff on that row for d in self.get('accounts'): if not d.credit and not d.debit and diff != 0: if diff>0: d.credit = diff elif diff<0: d.debit = diff flag = 1 # Set the diff in a new row if flag == 0 and diff != 0: jd = self.append('accounts', {}) if diff>0: jd.credit = abs(diff) elif diff<0: jd.debit = abs(diff) self.validate_debit_and_credit() def get_outstanding_invoices(self): self.set('accounts', []) total = 0 for d in self.get_values(): total += flt(d.outstanding_amount, self.precision("credit", "accounts")) jd1 = self.append('accounts', {}) jd1.account = d.account jd1.party = d.party if self.write_off_based_on == 'Accounts Receivable': jd1.party_type = "Customer" jd1.credit = flt(d.outstanding_amount, self.precision("credit", "accounts")) jd1.reference_type = "Sales Invoice" jd1.reference_name = cstr(d.name) elif self.write_off_based_on == 'Accounts Payable': jd1.party_type = "Supplier" jd1.debit = flt(d.outstanding_amount, self.precision("debit", "accounts")) jd1.reference_type = "Purchase Invoice" jd1.reference_name = cstr(d.name) jd2 = self.append('accounts', {}) if self.write_off_based_on == 'Accounts Receivable': jd2.debit = total elif self.write_off_based_on == 'Accounts Payable': jd2.credit = total self.validate_debit_and_credit() def get_values(self): cond = " and outstanding_amount <= {0}".format(self.write_off_amount) \ if flt(self.write_off_amount) > 0 else "" if self.write_off_based_on == 'Accounts Receivable': return frappe.db.sql("""select name, debit_to as account, customer as party, outstanding_amount from `tabSales Invoice` where docstatus = 1 and company = %s and outstanding_amount > 0 %s""" % ('%s', cond), self.company, as_dict=True) elif self.write_off_based_on == 'Accounts Payable': return frappe.db.sql("""select name, credit_to as account, supplier as party, outstanding_amount from `tabPurchase Invoice` where docstatus = 1 and company = %s and outstanding_amount > 0 %s""" % ('%s', cond), self.company, as_dict=True) def update_expense_claim(self): for d in self.accounts: if d.reference_type=="Expense Claim": amt = frappe.db.sql("""select sum(debit) as amt from `tabJournal Entry Account` where reference_type = "Expense Claim" and reference_name = %s and docstatus = 1""", d.reference_name ,as_dict=1)[0].amt frappe.db.set_value("Expense Claim", d.reference_name , "total_amount_reimbursed", amt) def validate_expense_claim(self): for d in self.accounts: if d.reference_type=="Expense Claim": sanctioned_amount, reimbursed_amount = frappe.db.get_value("Expense Claim", d.reference_name, ("total_sanctioned_amount", "total_amount_reimbursed")) pending_amount = flt(sanctioned_amount) - flt(reimbursed_amount) if d.debit > pending_amount: frappe.throw(_("Row No {0}: Amount cannot be greater than Pending Amount against Expense Claim {1}. Pending Amount is {2}".format(d.idx, d.reference_name, pending_amount))) def validate_credit_debit_note(self): if self.stock_entry: if frappe.db.get_value("Stock Entry", self.stock_entry, "docstatus") != 1: frappe.throw(_("Stock Entry {0} is not submitted").format(self.stock_entry)) if frappe.db.exists({"doctype": "Journal Entry", "stock_entry": self.stock_entry, "docstatus":1}): frappe.msgprint(_("Warning: Another {0} # {1} exists against stock entry {2}".format(self.voucher_type, self.name, self.stock_entry))) def validate_empty_accounts_table(self): if not self.get('accounts'): frappe.throw("Accounts table cannot be blank.") @frappe.whitelist() def get_default_bank_cash_account(company, voucher_type, mode_of_payment=None): from erpnext.accounts.doctype.sales_invoice.sales_invoice import get_bank_cash_account if mode_of_payment: account = get_bank_cash_account(mode_of_payment, company) if account.get("account"): account.update({"balance": get_balance_on(account.get("account"))}) return account if voucher_type=="Bank Entry": account = frappe.db.get_value("Company", company, "default_bank_account") if not account: account = frappe.db.get_value("Account", {"company": company, "account_type": "Bank", "is_group": 0}) elif voucher_type=="Cash Entry": account = frappe.db.get_value("Company", company, "default_cash_account") if not account: account = frappe.db.get_value("Account", {"company": company, "account_type": "Cash", "is_group": 0}) if account: return { "account": account, "balance": get_balance_on(account) } @frappe.whitelist() def get_payment_entry_from_sales_invoice(sales_invoice): """Returns new Journal Entry document as dict for given Sales Invoice""" from erpnext.accounts.utils import get_balance_on si = frappe.get_doc("Sales Invoice", sales_invoice) jv = get_payment_entry(si) jv.remark = 'Payment received against Sales Invoice {0}. {1}'.format(si.name, si.remarks) # credit customer jv.get("accounts")[0].account = si.debit_to jv.get("accounts")[0].party_type = "Customer" jv.get("accounts")[0].party = si.customer jv.get("accounts")[0].balance = get_balance_on(si.debit_to) jv.get("accounts")[0].party_balance = get_balance_on(party=si.customer, party_type="Customer") jv.get("accounts")[0].credit = si.outstanding_amount jv.get("accounts")[0].reference_type = si.doctype jv.get("accounts")[0].reference_name = si.name # debit bank jv.get("accounts")[1].debit = si.outstanding_amount return jv.as_dict() @frappe.whitelist() def get_payment_entry_from_purchase_invoice(purchase_invoice): """Returns new Journal Entry document as dict for given Purchase Invoice""" pi = frappe.get_doc("Purchase Invoice", purchase_invoice) jv = get_payment_entry(pi) jv.remark = 'Payment against Purchase Invoice {0}. {1}'.format(pi.name, pi.remarks) # credit supplier jv.get("accounts")[0].account = pi.credit_to jv.get("accounts")[0].party_type = "Supplier" jv.get("accounts")[0].party = pi.supplier jv.get("accounts")[0].balance = get_balance_on(pi.credit_to) jv.get("accounts")[0].party_balance = get_balance_on(party=pi.supplier, party_type="Supplier") jv.get("accounts")[0].debit = pi.outstanding_amount jv.get("accounts")[0].reference_type = pi.doctype jv.get("accounts")[0].reference_name = pi.name # credit bank jv.get("accounts")[1].credit = pi.outstanding_amount return jv.as_dict() @frappe.whitelist() def get_payment_entry_from_sales_order(sales_order): """Returns new Journal Entry document as dict for given Sales Order""" from erpnext.accounts.utils import get_balance_on from erpnext.accounts.party import get_party_account so = frappe.get_doc("Sales Order", sales_order) if flt(so.per_billed, 2) != 0.0: frappe.throw(_("Can only make payment against unbilled Sales Order")) jv = get_payment_entry(so) jv.remark = 'Advance payment received against Sales Order {0}.'.format(so.name) party_account = get_party_account(so.company, so.customer, "Customer") amount = flt(so.base_grand_total) - flt(so.advance_paid) # credit customer jv.get("accounts")[0].account = party_account jv.get("accounts")[0].party_type = "Customer" jv.get("accounts")[0].party = so.customer jv.get("accounts")[0].balance = get_balance_on(party_account) jv.get("accounts")[0].party_balance = get_balance_on(party=so.customer, party_type="Customer") jv.get("accounts")[0].credit = amount jv.get("accounts")[0].reference_type = so.doctype jv.get("accounts")[0].reference_name = so.name jv.get("accounts")[0].is_advance = "Yes" # debit bank jv.get("accounts")[1].debit = amount return jv.as_dict() @frappe.whitelist() def get_payment_entry_from_purchase_order(purchase_order): """Returns new Journal Entry document as dict for given Sales Order""" from erpnext.accounts.utils import get_balance_on from erpnext.accounts.party import get_party_account po = frappe.get_doc("Purchase Order", purchase_order) if flt(po.per_billed, 2) != 0.0: frappe.throw(_("Can only make payment against unbilled Sales Order")) jv = get_payment_entry(po) jv.remark = 'Advance payment made against Purchase Order {0}.'.format(po.name) party_account = get_party_account(po.company, po.supplier, "Supplier") amount = flt(po.base_grand_total) - flt(po.advance_paid) # credit customer jv.get("accounts")[0].account = party_account jv.get("accounts")[0].party_type = "Supplier" jv.get("accounts")[0].party = po.supplier jv.get("accounts")[0].balance = get_balance_on(party_account) jv.get("accounts")[0].party_balance = get_balance_on(party=po.supplier, party_type="Supplier") jv.get("accounts")[0].debit = amount jv.get("accounts")[0].reference_type = po.doctype jv.get("accounts")[0].reference_name = po.name jv.get("accounts")[0].is_advance = "Yes" # debit bank jv.get("accounts")[1].credit = amount return jv.as_dict() def get_payment_entry(doc): bank_account = get_default_bank_cash_account(doc.company, "Bank Entry") jv = frappe.new_doc('Journal Entry') jv.voucher_type = 'Bank Entry' jv.company = doc.company jv.fiscal_year = doc.fiscal_year jv.append("accounts") d2 = jv.append("accounts") if bank_account: d2.account = bank_account["account"] d2.balance = bank_account["balance"] return jv @frappe.whitelist() def get_opening_accounts(company): """get all balance sheet accounts for opening entry""" accounts = frappe.db.sql_list("""select name from tabAccount where is_group=0 and report_type='Balance Sheet' and company=%s""", company) return [{"account": a, "balance": get_balance_on(a)} for a in accounts] def get_against_jv(doctype, txt, searchfield, start, page_len, filters): return frappe.db.sql("""select jv.name, jv.posting_date, jv.user_remark from `tabJournal Entry` jv, `tabJournal Entry Account` jv_detail where jv_detail.parent = jv.name and jv_detail.account = %s and ifnull(jv_detail.party, '') = %s and ifnull(jv_detail.reference_type, '') = '' and jv.docstatus = 1 and jv.{0} like %s order by jv.name desc limit %s, %s""".format(searchfield), (filters.get("account"), cstr(filters.get("party")), "%{0}%".format(txt), start, page_len)) @frappe.whitelist() def get_outstanding(args): if not frappe.has_permission("Account"): frappe.msgprint(_("No Permission"), raise_exception=1) args = eval(args) if args.get("doctype") == "Journal Entry": condition = " and party=%(party)s" if args.get("party") else "" against_jv_amount = frappe.db.sql(""" select sum(ifnull(debit, 0)) - sum(ifnull(credit, 0)) from `tabJournal Entry Account` where parent=%(docname)s and account=%(account)s {0} and ifnull(reference_type, '')=''""".format(condition), args) against_jv_amount = flt(against_jv_amount[0][0]) if against_jv_amount else 0 return { ("credit" if against_jv_amount > 0 else "debit"): abs(against_jv_amount) } elif args.get("doctype") == "Sales Invoice": outstanding_amount = flt(frappe.db.get_value("Sales Invoice", args["docname"], "outstanding_amount")) return { ("credit" if outstanding_amount > 0 else "debit"): abs(outstanding_amount) } elif args.get("doctype") == "Purchase Invoice": outstanding_amount = flt(frappe.db.get_value("Purchase Invoice", args["docname"], "outstanding_amount")) return { ("debit" if outstanding_amount > 0 else "credit"): abs(outstanding_amount) } @frappe.whitelist() def get_party_account_and_balance(company, party_type, party): if not frappe.has_permission("Account"): frappe.msgprint(_("No Permission"), raise_exception=1) from erpnext.accounts.party import get_party_account account = get_party_account(company, party, party_type) account_balance = get_balance_on(account=account) party_balance = get_balance_on(party_type=party_type, party=party) return { "account": account, "balance": account_balance, "party_balance": party_balance } @frappe.whitelist() def get_account_balance_and_party_type(account, date): """Returns dict of account balance and party type to be set in Journal Entry on selection of account.""" if not frappe.has_permission("Account"): frappe.msgprint(_("No Permission"), raise_exception=1) account_type = frappe.db.get_value("Account", account, "account_type") return { "balance": get_balance_on(account, date), "party_type": {"Receivable":"Customer", "Payable":"Supplier"}.get(account_type, "") }
huongttlan/bokeh
refs/heads/master
bokeh/charts/builder/bar_builder.py
43
"""This is the Bokeh charts interface. It gives you a high level API to build complex plot is a simple way. This is the Bar class which lets you build your Bar charts just passing the arguments to the Chart class and calling the proper functions. It also add a new chained stacked method. """ #----------------------------------------------------------------------------- # Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved. # # Powered by the Bokeh Development Team. # # The full license is in the file LICENSE.txt, distributed with this software. #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- from __future__ import absolute_import, print_function, division try: import numpy as np except ImportError: raise RuntimeError("bokeh.charts Bar chart requires NumPy.") from ..utils import chunk, cycle_colors from .._builder import Builder, create_and_build from ...models import ColumnDataSource, FactorRange, GlyphRenderer, Range1d from ...models.glyphs import Rect from ...properties import Any, Bool, Either, List #----------------------------------------------------------------------------- # Classes and functions #----------------------------------------------------------------------------- def Bar(values, cat=None, stacked=False, xscale="categorical", yscale="linear", xgrid=False, ygrid=True, continuous_range=None, **kw): """ Create a Bar chart using :class:`BarBuilder <bokeh.charts.builder.bar_builder.BarBuilder>` render the geometry from values, cat and stacked. Args: values (iterable): iterable 2d representing the data series values matrix. cat (list or bool, optional): list of string representing the categories. (Defaults to None) stacked (bool, optional): to see the bars stacked or grouped. (Defaults to False, so grouping is assumed) continuous_range(Range1d, optional): Custom continuous_range to be used. (Defaults to None) In addition the the parameters specific to this chart, :ref:`userguide_charts_generic_arguments` are also accepted as keyword parameters. Returns: a new :class:`Chart <bokeh.charts.Chart>` Examples: .. bokeh-plot:: :source-position: above from collections import OrderedDict from bokeh.charts import Bar, output_file, show # (dict, OrderedDict, lists, arrays and DataFrames are valid inputs) xyvalues = OrderedDict() xyvalues['python']=[-2, 5] xyvalues['pypy']=[12, 40] xyvalues['jython']=[22, 30] cat = ['1st', '2nd'] bar = Bar(xyvalues, cat, title="Stacked bars", xlabel="category", ylabel="language") output_file("stacked_bar.html") show(bar) """ if continuous_range and not isinstance(continuous_range, Range1d): raise ValueError( "continuous_range must be an instance of bokeh.models.ranges.Range1d" ) # The continuous_range is the y_range (until we implement HBar charts) y_range = continuous_range return create_and_build( BarBuilder, values, cat=cat, stacked=stacked, xscale=xscale, yscale=yscale, xgrid=xgrid, ygrid=ygrid, y_range=y_range, **kw ) class BarBuilder(Builder): """This is the Bar class and it is in charge of plotting Bar chart (grouped and stacked) in an easy and intuitive way. Essentially, it provides a way to ingest the data, make the proper calculations and push the references into a source object. We additionally make calculations for the ranges. And finally add the needed glyphs (rects) taking the references from the source. The x_range is categorical, and is made either from the cat argument or from the indexes of the passed values if no cat is supplied. The y_range can be supplied as the parameter continuous_range, or will be calculated as a linear range (Range1d) based on the supplied values using the following rules: * with all positive data: start = 0, end = 1.1 * max * with all negative data: start = 1.1 * min, end = 0 * with mixed sign data: start = 1.1 * min, end = 1.1 * max """ cat = Either(Bool, List(Any), help=""" List of string representing the categories. (Defaults to None.) """) stacked = Bool(False, help=""" Whether to stack the bars. (Defaults to False) If True, bars are draw as a stack, to show the relationship of parts to a whole. Otherwise, bars are grouped on the same chart. """) def _process_data(self): """Take the Bar data from the input **value. It calculates the chart properties accordingly. Then build a dict containing references to all the calculated points to be used by the rect glyph inside the ``_yield_renderers`` method. """ if not self.cat: self.cat = [str(x) for x in self._values.index] width = [0.8] * len(self.cat) # width should decrease proportionally to the value length. # 1./len(value) doesn't work well as the width needs to decrease a # little bit faster width_cat = [min(0.2, (1. / len(self._values)) ** 1.1)] * len(self.cat) zero = np.zeros(len(self.cat)) self._data = dict( cat=self.cat, width=width, width_cat=width_cat, zero=zero ) # list to save all the groups available in the incomming input grouping step = np.linspace(0, 1.0, len(self._values.keys()) + 1, endpoint=False) self._groups.extend(self._values.keys()) for i, (val, values) in enumerate(self._values.items()): self.set_and_get("", val, list(values)) mid = np.array(values) / 2 self.set_and_get("mid", val, mid) self.set_and_get("stacked", val, zero + mid) # Grouped grouped = [c + ":" + str(step[i + 1]) for c in self.cat] self.set_and_get("cat", val, grouped) # Stacked zero += values def _set_sources(self): """Push the Bar data into the ColumnDataSource and calculate the proper ranges. """ self._source = ColumnDataSource(self._data) self.x_range = FactorRange(factors=self._source.data["cat"]) if not self.y_range: if self.stacked: data = np.array(self._data['zero']) else: cats = [i for i in self._attr if not i.startswith(("mid", "stacked", "cat"))] data = np.array([self._data[cat] for cat in cats]) all_positive = True if np.all(data > 0) else False all_negative = True if np.all(data < 0) else False # Set the start value if all_positive: start = 0 else: start = 1.1 * data.min() # Will always be negative # Set the end value if all_negative: end = 0 else: end = 1.1 * data.max() self.y_range = Range1d(start=start, end=end) def _yield_renderers(self): """Use the rect glyphs to display the bars. Takes reference points from data loaded at the ColumnDataSource. """ quartets = list(chunk(self._attr, 4)) colors = cycle_colors(quartets, self.palette) # quartet elements are: [data, mid, stacked, cat] for i, quartet in enumerate(quartets): if self.stacked: glyph = Rect( x="cat", y=quartet[2], width="width", height=quartet[0], fill_color=colors[i], fill_alpha=0.7, line_color="white" ) else: # Grouped glyph = Rect( x=quartet[3], y=quartet[1], width="width_cat", height=quartet[0], fill_color=colors[i], fill_alpha=0.7, line_color="white" ) renderer = GlyphRenderer(data_source=self._source, glyph=glyph) self._legends.append((self._groups[i], [renderer])) yield renderer
xombiemp/CouchPotatoServer
refs/heads/master
libs/pyutil/find_exe.py
106
import warnings import os, sys from twisted.python.procutils import which def find_exe(exename): """ Look for something named exename or exename + ".py". This is a kludge. @return: a list containing one element which is the path to the exename (if it is thought to be executable), or else the first element being sys.executable and the second element being the path to the exename + ".py", or else return False if one can't be found """ warnings.warn("deprecated", DeprecationWarning) exes = which(exename) exe = exes and exes[0] if not exe: exe = os.path.join(sys.prefix, 'scripts', exename + '.py') if os.path.exists(exe): path, ext = os.path.splitext(exe) if ext.lower() in [".exe", ".bat",]: cmd = [exe,] else: cmd = [sys.executable, exe,] return cmd else: return False
mosaic-cloud/mosaic-distribution-dependencies
refs/heads/development
dependencies/mozilla-js/1.8.5/js/src/jit-test/progressbar.py
9
# Text progress bar library, like curl or scp. import sys, datetime class ProgressBar: def __init__(self, label, limit, label_width=12): self.label = label self.limit = limit self.label_width = label_width self.cur = 0 self.t0 = datetime.datetime.now() self.barlen = 64 - self.label_width self.fmt = '\r%-' + str(label_width) + 's %3d%% %-' + str(self.barlen) + 's| %6.1fs' def update(self, value): self.cur = value pct = int(100.0 * self.cur / self.limit) barlen = int(1.0 * self.barlen * self.cur / self.limit) - 1 bar = '='*barlen + '>' dt = datetime.datetime.now() - self.t0 dt = dt.seconds + dt.microseconds * 1e-6 sys.stdout.write(self.fmt%(self.label[:self.label_width], pct, bar, dt)) sys.stdout.flush() def finish(self): self.update(self.limit) sys.stdout.write('\n') if __name__ == '__main__': pb = ProgressBar('test', 12) for i in range(12): pb.update(i) time.sleep(0.5) pb.finish()
rdbhost/Rdbhdb
refs/heads/master
unittests-py2/test_rdbhdb_compressed.py
1
#!/usr/bin/env python ''' unit test suite for compressed features of rdbhdb''' import unittest import time import sys, os import accounts sys.path.insert(0, '..\lib') from rdbhdb import rdbhdb need_version = '0.11.0' class test_Rdbhdb_compressedRequest(unittest.TestCase): driver = rdbhdb # get choice of server from environment HOST = os.environ.get('RDBHOST_TEST', "dev.rdbhost.com").strip("'") connect_args = () connect_kw_args = { 'role': accounts.demo['role'], 'authcode': accounts.demo['authcode'], 'host': HOST} table_prefix = 'compressed_' # If you need to specify a prefix for tables ddl1 = '''CREATE TABLE %sbig (descr TEXT, idx INTEGER);''' % table_prefix xddl1 = 'DROP TABLE %sbig;' % table_prefix # Some drivers may need to override these helpers, for example adding # a 'commit' after the execute. def executeDDL1(self, cursor): cursor.execute(self.ddl1) def setUp(self): # Call superclass setUp In case this does something in the # future try: con = self._connect() con.close() except Exception as e: print 'connection not made. %s db must be created online.' % e[0] sys.exit(2) def tearDown(self): ''' self.drivers should override this method to perform required cleanup if any is necessary, such as deleting the test database. The default drops the tables that may be created. ''' con = self._connect() try: cur = con.cursor() for ddl in (self.xddl1, ): try: cur.execute(ddl) con.commit() except self.driver.Error: # Assume table didn't exist. Other tests will check if # execute is busted. pass finally: con.close() def _connect(self): try: return self.driver.connect(*self.connect_args, **self.connect_kw_args) except AttributeError: self.fail("No connect method found in self.driver module") def test0_host(self): print >> sys.stderr, 'using server', self.HOST def test1_version(self): """Verify correct API module version in use.""" lVersion = rdbhdb.__version__.split('.') nVersion = need_version.split('.') self.assert_(lVersion >= nVersion, rdbhdb.__version__) def test_Compressed(self): con = self._connect() try: cur = con.cursor() # cursor.fetchone should raise an Error if called after # executing a query that cannnot return rows self.executeDDL1(cur) cur.execute('select idx from %sbig' % self.table_prefix) self.assertEqual(cur.fetchone(), None, 'cursor.fetchone should return None if a query retrieves no rows') self.failUnless(cur.rowcount in (-1, 0)) stuff = "asjdfasdl;kfjasdkl;fj asdklfh asdlkfj asdklfj asdklfj asdklf adddsdklfasdfas f" + \ "asjkdf askldfjasdlkfjasdlkfj asdklfjasdlkfj asdklfjasdlkfj asdlfj asdlfjasdlkf" + \ "asldkjfasdl;kfjaskldfjasdklfjasdklfjasdklfjasdfasdfkljasdklfjasdklfjasdlkfjsdl" qs = [] args = [] for i in range(15): qs.append('INSERT INTO %sbig (idx, descr) VALUES(%%s, %%s);' % self.table_prefix) assert 235 > len(stuff) > 230, len(stuff) args.extend([i+1, stuff]) q = '\n'.join(qs) self.assert_(len(q)>150, len(q)) self.assert_(sum([len(a) for a in args if type(a) == type('')]) > 2000) self.assert_(len(args) == 30) self.assert_(not any([a for a in args if type(a) == type('') and len(a)>300])) cur.execute(q, args) self.assertRaises(self.driver.Error, cur.fetchone) cur.execute('select count(*) from %sbig' % self.table_prefix) r = cur.fetchone() self.assertEqual(len(r), 1, 'cursor.fetchone should have retrieved a single row') self.assertEqual(r[0], 15, 'cursor.fetchone retrieved incorrect data %s' % r[0]) self.failUnless(cur.rowcount in (-1, 1)) finally: con.close() class test_Rdbhdb_compressedRequest_ws(test_Rdbhdb_compressedRequest): connect_kw_args = { 'role': accounts.demo['role'], 'authcode': accounts.demo['authcode'], 'host': test_Rdbhdb_compressedRequest.HOST, 'useWebsocket': True } if __name__ == '__main__': unittest.main()
maropu/spark
refs/heads/master
python/pyspark/pandas/tests/data_type_ops/test_datetime_ops.py
13
# # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import datetime import numpy as np import pandas as pd from pandas.api.types import CategoricalDtype from pyspark import pandas as ps from pyspark.pandas.config import option_context from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils from pyspark.testing.pandasutils import PandasOnSparkTestCase class DatetimeOpsTest(PandasOnSparkTestCase, TestCasesUtils): @property def pser(self): return pd.Series(pd.date_range("1994-1-31 10:30:15", periods=3, freq="M")) @property def psser(self): return ps.from_pandas(self.pser) @property def some_datetime(self): return datetime.datetime(1994, 1, 31, 10, 30, 00) def test_add(self): self.assertRaises(TypeError, lambda: self.psser + "x") self.assertRaises(TypeError, lambda: self.psser + 1) self.assertRaises(TypeError, lambda: self.psser + self.some_datetime) with option_context("compute.ops_on_diff_frames", True): for psser in self.pssers: self.assertRaises(TypeError, lambda: self.psser + psser) def test_sub(self): self.assertRaises(TypeError, lambda: self.psser - "x") self.assertRaises(TypeError, lambda: self.psser - 1) self.assert_eq( (self.pser - self.some_datetime).dt.total_seconds().astype("int"), self.psser - self.some_datetime, ) with option_context("compute.ops_on_diff_frames", True): for pser, psser in self.pser_psser_pairs: if pser.dtype == np.dtype("<M8[ns]"): self.assert_eq( (self.pser - pser).dt.total_seconds().astype("int"), (self.psser - psser).sort_index(), ) else: self.assertRaises(TypeError, lambda: self.psser - psser) def test_mul(self): self.assertRaises(TypeError, lambda: self.psser * "x") self.assertRaises(TypeError, lambda: self.psser * 1) self.assertRaises(TypeError, lambda: self.psser * self.some_datetime) with option_context("compute.ops_on_diff_frames", True): for psser in self.pssers: self.assertRaises(TypeError, lambda: self.psser * psser) def test_truediv(self): self.assertRaises(TypeError, lambda: self.psser / "x") self.assertRaises(TypeError, lambda: self.psser / 1) self.assertRaises(TypeError, lambda: self.psser / self.some_datetime) with option_context("compute.ops_on_diff_frames", True): for psser in self.pssers: self.assertRaises(TypeError, lambda: self.psser / psser) def test_floordiv(self): self.assertRaises(TypeError, lambda: self.psser // "x") self.assertRaises(TypeError, lambda: self.psser // 1) self.assertRaises(TypeError, lambda: self.psser // self.some_datetime) with option_context("compute.ops_on_diff_frames", True): for psser in self.pssers: self.assertRaises(TypeError, lambda: self.psser // psser) def test_mod(self): self.assertRaises(TypeError, lambda: self.psser % "x") self.assertRaises(TypeError, lambda: self.psser % 1) self.assertRaises(TypeError, lambda: self.psser % self.some_datetime) with option_context("compute.ops_on_diff_frames", True): for psser in self.pssers: self.assertRaises(TypeError, lambda: self.psser % psser) def test_pow(self): self.assertRaises(TypeError, lambda: self.psser ** "x") self.assertRaises(TypeError, lambda: self.psser ** 1) self.assertRaises(TypeError, lambda: self.psser ** self.some_datetime) with option_context("compute.ops_on_diff_frames", True): for psser in self.pssers: self.assertRaises(TypeError, lambda: self.psser ** psser) def test_radd(self): self.assertRaises(TypeError, lambda: "x" + self.psser) self.assertRaises(TypeError, lambda: 1 + self.psser) self.assertRaises(TypeError, lambda: self.some_datetime + self.psser) def test_rsub(self): self.assertRaises(TypeError, lambda: "x" - self.psser) self.assertRaises(TypeError, lambda: 1 - self.psser) self.assert_eq( (self.some_datetime - self.pser).dt.total_seconds().astype("int"), self.some_datetime - self.psser, ) def test_rmul(self): self.assertRaises(TypeError, lambda: "x" * self.psser) self.assertRaises(TypeError, lambda: 1 * self.psser) self.assertRaises(TypeError, lambda: self.some_datetime * self.psser) def test_rtruediv(self): self.assertRaises(TypeError, lambda: "x" / self.psser) self.assertRaises(TypeError, lambda: 1 / self.psser) self.assertRaises(TypeError, lambda: self.some_datetime / self.psser) def test_rfloordiv(self): self.assertRaises(TypeError, lambda: "x" // self.psser) self.assertRaises(TypeError, lambda: 1 // self.psser) self.assertRaises(TypeError, lambda: self.some_datetime // self.psser) def test_rmod(self): self.assertRaises(TypeError, lambda: 1 % self.psser) self.assertRaises(TypeError, lambda: self.some_datetime % self.psser) def test_rpow(self): self.assertRaises(TypeError, lambda: "x" ** self.psser) self.assertRaises(TypeError, lambda: 1 ** self.psser) self.assertRaises(TypeError, lambda: self.some_datetime ** self.psser) def test_and(self): self.assertRaises(TypeError, lambda: self.psser & True) self.assertRaises(TypeError, lambda: self.psser & False) self.assertRaises(TypeError, lambda: self.psser & self.psser) def test_rand(self): self.assertRaises(TypeError, lambda: True & self.psser) self.assertRaises(TypeError, lambda: False & self.psser) def test_or(self): self.assertRaises(TypeError, lambda: self.psser | True) self.assertRaises(TypeError, lambda: self.psser | False) self.assertRaises(TypeError, lambda: self.psser | self.psser) def test_ror(self): self.assertRaises(TypeError, lambda: True | self.psser) self.assertRaises(TypeError, lambda: False | self.psser) def test_from_to_pandas(self): data = pd.date_range("1994-1-31 10:30:15", periods=3, freq="M") pser = pd.Series(data) psser = ps.Series(data) self.assert_eq(pser, psser.to_pandas()) self.assert_eq(ps.from_pandas(pser), psser) def test_isnull(self): self.assert_eq(self.pser.isnull(), self.psser.isnull()) def test_astype(self): pser = self.pser psser = self.psser self.assert_eq(pser.astype(str), psser.astype(str)) self.assert_eq(pser.astype("category"), psser.astype("category")) cat_type = CategoricalDtype(categories=["a", "b", "c"]) self.assert_eq(pser.astype(cat_type), psser.astype(cat_type)) if __name__ == "__main__": import unittest from pyspark.pandas.tests.data_type_ops.test_datetime_ops import * # noqa: F401 try: import xmlrunner # type: ignore[import] testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) except ImportError: testRunner = None unittest.main(testRunner=testRunner, verbosity=2)
leoliujie/odoo
refs/heads/8.0
addons/gamification/tests/__init__.py
268
# -*- coding: utf-8 -*- ############################################################################## # # OpenERP, Open Source Business Applications # Copyright (c) 2013 OpenERP S.A. <http://openerp.com> # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as # published by the Free Software Foundation, either version 3 of the # License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ############################################################################## from . import test_challenge
nicememory/pie
refs/heads/master
pyglet/tests/extlibs/future/py2_3/future/moves/urllib/response.py
70
from future import standard_library from future.utils import PY3 if PY3: from urllib.response import * else: __future_module__ = True with standard_library.suspend_hooks(): from urllib import (addbase, addclosehook, addinfo, addinfourl)
chaluemwut/fbserver
refs/heads/master
venv/lib/python2.7/site-packages/sklearn/ensemble/base.py
2
""" Base class for ensemble-based estimators. """ # Authors: Gilles Louppe # License: BSD 3 clause import numpy as np from ..base import clone from ..base import BaseEstimator from ..base import MetaEstimatorMixin from ..externals.joblib import cpu_count class BaseEnsemble(BaseEstimator, MetaEstimatorMixin): """Base class for all ensemble classes. Warning: This class should not be used directly. Use derived classes instead. Parameters ---------- base_estimator : object, optional (default=None) The base estimator from which the ensemble is built. n_estimators : integer The number of estimators in the ensemble. estimator_params : list of strings The list of attributes to use as parameters when instantiating a new base estimator. If none are given, default parameters are used. Attributes ---------- `base_estimator_`: list of estimators The base estimator from which the ensemble is grown. `estimators_`: list of estimators The collection of fitted base estimators. """ def __init__(self, base_estimator, n_estimators=10, estimator_params=tuple()): # Set parameters self.base_estimator = base_estimator self.n_estimators = n_estimators self.estimator_params = estimator_params # Don't instantiate estimators now! Parameters of base_estimator might # still change. Eg., when grid-searching with the nested object syntax. # This needs to be filled by the derived classes. self.estimators_ = [] def _validate_estimator(self, default=None): """Check the estimator and the n_estimator attribute, set the `base_estimator_` attribute.""" if self.n_estimators <= 0: raise ValueError("n_estimators must be greater than zero, " "got {0}.".format(self.n_estimators)) if self.base_estimator is not None: self.base_estimator_ = self.base_estimator else: self.base_estimator_ = default if self.base_estimator_ is None: raise ValueError("base_estimator cannot be None") def _make_estimator(self, append=True): """Make and configure a copy of the `base_estimator_` attribute. Warning: This method should be used to properly instantiate new sub-estimators. """ estimator = clone(self.base_estimator_) estimator.set_params(**dict((p, getattr(self, p)) for p in self.estimator_params)) if append: self.estimators_.append(estimator) return estimator def __len__(self): """Returns the number of estimators in the ensemble.""" return len(self.estimators_) def __getitem__(self, index): """Returns the index'th estimator in the ensemble.""" return self.estimators_[index] def __iter__(self): """Returns iterator over estimators in the ensemble.""" return iter(self.estimators_) def _partition_estimators(ensemble): """Private function used to partition estimators between jobs.""" # Compute the number of jobs if ensemble.n_jobs == -1: n_jobs = min(cpu_count(), ensemble.n_estimators) else: n_jobs = min(ensemble.n_jobs, ensemble.n_estimators) # Partition estimators between jobs n_estimators = (ensemble.n_estimators // n_jobs) * np.ones(n_jobs, dtype=np.int) n_estimators[:ensemble.n_estimators % n_jobs] += 1 starts = np.cumsum(n_estimators) return n_jobs, n_estimators.tolist(), [0] + starts.tolist()
ChinaQuants/zipline
refs/heads/master
zipline/protocol.py
3
# # Copyright 2013 Quantopian, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from copy import copy from six import iteritems, iterkeys import pandas as pd import numpy as np from . utils.protocol_utils import Enum from . utils.math_utils import nanstd, nanmean, nansum from zipline.utils.algo_instance import get_algo_instance from zipline.utils.serialization_utils import ( VERSION_LABEL ) # Datasource type should completely determine the other fields of a # message with its type. DATASOURCE_TYPE = Enum( 'AS_TRADED_EQUITY', 'MERGER', 'SPLIT', 'DIVIDEND', 'TRADE', 'TRANSACTION', 'ORDER', 'EMPTY', 'DONE', 'CUSTOM', 'BENCHMARK', 'COMMISSION', 'CLOSE_POSITION' ) # Expected fields/index values for a dividend Series. DIVIDEND_FIELDS = [ 'declared_date', 'ex_date', 'gross_amount', 'net_amount', 'pay_date', 'payment_sid', 'ratio', 'sid', ] # Expected fields/index values for a dividend payment Series. DIVIDEND_PAYMENT_FIELDS = [ 'id', 'payment_sid', 'cash_amount', 'share_count', ] def dividend_payment(data=None): """ Take a dictionary whose values are in DIVIDEND_PAYMENT_FIELDS and return a series representing the payment of a dividend. Ids are assigned to each historical dividend in PerformanceTracker.update_dividends. They are guaranteed to be unique integers with the context of a single simulation. If @data is non-empty, a id is required to identify the historical dividend associated with this payment. Additionally, if @data is non-empty, either data['cash_amount'] should be nonzero or data['payment_sid'] should be an asset identifier and data['share_count'] should be nonzero. The returned Series is given its id value as a name so that concatenating payments results in a DataFrame indexed by id. (Note, however, that the name value is not used to construct an index when this series is returned by function passed to `DataFrame.apply`. In such a case, pandas preserves the index of the DataFrame on which `apply` is being called.) """ return pd.Series( data=data, name=data['id'] if data is not None else None, index=DIVIDEND_PAYMENT_FIELDS, dtype=object, ) class Event(object): def __init__(self, initial_values=None): if initial_values: self.__dict__ = initial_values def __getitem__(self, name): return getattr(self, name) def __setitem__(self, name, value): setattr(self, name, value) def __delitem__(self, name): delattr(self, name) def keys(self): return self.__dict__.keys() def __eq__(self, other): return hasattr(other, '__dict__') and self.__dict__ == other.__dict__ def __contains__(self, name): return name in self.__dict__ def __repr__(self): return "Event({0})".format(self.__dict__) def to_series(self, index=None): return pd.Series(self.__dict__, index=index) class Order(Event): pass class Portfolio(object): def __init__(self): self.capital_used = 0.0 self.starting_cash = 0.0 self.portfolio_value = 0.0 self.pnl = 0.0 self.returns = 0.0 self.cash = 0.0 self.positions = Positions() self.start_date = None self.positions_value = 0.0 def __getitem__(self, key): return self.__dict__[key] def __repr__(self): return "Portfolio({0})".format(self.__dict__) def __getstate__(self): state_dict = copy(self.__dict__) # Have to convert to primitive dict state_dict['positions'] = dict(self.positions) STATE_VERSION = 1 state_dict[VERSION_LABEL] = STATE_VERSION return state_dict def __setstate__(self, state): OLDEST_SUPPORTED_STATE = 1 version = state.pop(VERSION_LABEL) if version < OLDEST_SUPPORTED_STATE: raise BaseException("Portfolio saved state is too old.") self.positions = Positions() self.positions.update(state.pop('positions')) self.__dict__.update(state) class Account(object): ''' The account object tracks information about the trading account. The values are updated as the algorithm runs and its keys remain unchanged. If connected to a broker, one can update these values with the trading account values as reported by the broker. ''' def __init__(self): self.settled_cash = 0.0 self.accrued_interest = 0.0 self.buying_power = float('inf') self.equity_with_loan = 0.0 self.total_positions_value = 0.0 self.regt_equity = 0.0 self.regt_margin = float('inf') self.initial_margin_requirement = 0.0 self.maintenance_margin_requirement = 0.0 self.available_funds = 0.0 self.excess_liquidity = 0.0 self.cushion = 0.0 self.day_trades_remaining = float('inf') self.leverage = 0.0 self.net_leverage = 0.0 self.net_liquidation = 0.0 def __getitem__(self, key): return self.__dict__[key] def __repr__(self): return "Account({0})".format(self.__dict__) def __getstate__(self): state_dict = copy(self.__dict__) STATE_VERSION = 1 state_dict[VERSION_LABEL] = STATE_VERSION return state_dict def __setstate__(self, state): OLDEST_SUPPORTED_STATE = 1 version = state.pop(VERSION_LABEL) if version < OLDEST_SUPPORTED_STATE: raise BaseException("Account saved state is too old.") self.__dict__.update(state) class Position(object): def __init__(self, sid): self.sid = sid self.amount = 0 self.cost_basis = 0.0 # per share self.last_sale_price = 0.0 def __getitem__(self, key): return self.__dict__[key] def __repr__(self): return "Position({0})".format(self.__dict__) def __getstate__(self): state_dict = copy(self.__dict__) STATE_VERSION = 1 state_dict[VERSION_LABEL] = STATE_VERSION return state_dict def __setstate__(self, state): OLDEST_SUPPORTED_STATE = 1 version = state.pop(VERSION_LABEL) if version < OLDEST_SUPPORTED_STATE: raise BaseException("Protocol Position saved state is too old.") self.__dict__.update(state) class Positions(dict): def __missing__(self, key): pos = Position(key) self[key] = pos return pos class SIDData(object): # Cache some data on the class so that this is shared for all instances of # siddata. # The dt where we cached the history. _history_cache_dt = None # _history_cache is a a dict mapping fields to pd.DataFrames. This is the # most data we have for a given field for the _history_cache_dt. _history_cache = {} # This is the cache that is used for returns. This will have a different # structure than the other history cache as this is always daily. _returns_cache_dt = None _returns_cache = None # The last dt that we needed to cache the number of minutes. _minute_bar_cache_dt = None # If we are in minute mode, there is some cost associated with computing # the number of minutes that we need to pass to the bar count of history. # This will remain constant for a given bar and day count. # This maps days to number of minutes. _minute_bar_cache = {} def __init__(self, sid, initial_values=None): self._sid = sid self._freqstr = None # To check if we have data, we use the __len__ which depends on the # __dict__. Because we are foward defining the attributes needed, we # need to account for their entrys in the __dict__. # We will add 1 because we need to account for the _initial_len entry # itself. self._initial_len = len(self.__dict__) + 1 if initial_values: self.__dict__.update(initial_values) @property def datetime(self): """ Provides an alias from data['foo'].datetime -> data['foo'].dt `datetime` was previously provided by adding a seperate `datetime` member of the SIDData object via a generator that wrapped the incoming data feed and added the field to each equity event. This alias is intended to be temporary, to provide backwards compatibility with existing algorithms, but should be considered deprecated, and may be removed in the future. """ return self.dt def get(self, name, default=None): return self.__dict__.get(name, default) def __getitem__(self, name): return self.__dict__[name] def __setitem__(self, name, value): self.__dict__[name] = value def __len__(self): return len(self.__dict__) - self._initial_len def __contains__(self, name): return name in self.__dict__ def __repr__(self): return "SIDData({0})".format(self.__dict__) def _get_buffer(self, bars, field='price', raw=False): """ Gets the result of history for the given number of bars and field. This will cache the results internally. """ cls = self.__class__ algo = get_algo_instance() now = algo.datetime if now != cls._history_cache_dt: # For a given dt, the history call for this field will not change. # We have a new dt, so we should reset the cache. cls._history_cache_dt = now cls._history_cache = {} if field not in self._history_cache \ or bars > len(cls._history_cache[field][0].index): # If we have never cached this field OR the amount of bars that we # need for this field is greater than the amount we have cached, # then we need to get more history. hst = algo.history( bars, self._freqstr, field, ffill=True, ) # Assert that the column holds ints, not security objects. if not isinstance(self._sid, str): hst.columns = hst.columns.astype(int) self._history_cache[field] = (hst, hst.values, hst.columns) # Slice of only the bars needed. This is because we strore the LARGEST # amount of history for the field, and we might request less than the # largest from the cache. buffer_, values, columns = cls._history_cache[field] if raw: sid_index = columns.get_loc(self._sid) return values[-bars:, sid_index] else: return buffer_[self._sid][-bars:] def _get_bars(self, days): """ Gets the number of bars needed for the current number of days. Figures this out based on the algo datafrequency and caches the result. This caches the result by replacing this function on the object. This means that after the first call to _get_bars, this method will point to a new function object. """ def daily_get_max_bars(days): return days def minute_get_max_bars(days): # max number of minute. regardless of current days or short # sessions return days * 390 def daily_get_bars(days): return days def minute_get_bars(days): cls = self.__class__ now = get_algo_instance().datetime if now != cls._minute_bar_cache_dt: cls._minute_bar_cache_dt = now cls._minute_bar_cache = {} if days not in cls._minute_bar_cache: # Cache this calculation to happen once per bar, even if we # use another transform with the same number of days. env = get_algo_instance().trading_environment prev = env.previous_trading_day(now) ds = env.days_in_range( env.add_trading_days(-days + 2, prev), prev, ) # compute the number of minutes in the (days - 1) days before # today. # 210 minutes in a an early close and 390 in a full day. ms = sum(210 if d in env.early_closes else 390 for d in ds) # Add the number of minutes for today. ms += int( (now - env.get_open_and_close(now)[0]).total_seconds() / 60 ) cls._minute_bar_cache[days] = ms + 1 # Account for this minute return cls._minute_bar_cache[days] if get_algo_instance().sim_params.data_frequency == 'daily': self._freqstr = '1d' # update this method to point to the daily variant. self._get_bars = daily_get_bars self._get_max_bars = daily_get_max_bars else: self._freqstr = '1m' # update this method to point to the minute variant. self._get_bars = minute_get_bars self._get_max_bars = minute_get_max_bars # Not actually recursive because we have already cached the new method. return self._get_bars(days) def mavg(self, days): bars = self._get_bars(days) max_bars = self._get_max_bars(days) prices = self._get_buffer(max_bars, raw=True)[-bars:] return nanmean(prices) def stddev(self, days): bars = self._get_bars(days) max_bars = self._get_max_bars(days) prices = self._get_buffer(max_bars, raw=True)[-bars:] return nanstd(prices, ddof=1) def vwap(self, days): bars = self._get_bars(days) max_bars = self._get_max_bars(days) prices = self._get_buffer(max_bars, raw=True)[-bars:] vols = self._get_buffer(max_bars, field='volume', raw=True)[-bars:] vol_sum = nansum(vols) try: ret = nansum(prices * vols) / vol_sum except ZeroDivisionError: ret = np.nan return ret def returns(self): algo = get_algo_instance() now = algo.datetime if now != self._returns_cache_dt: self._returns_cache_dt = now self._returns_cache = algo.history(2, '1d', 'price', ffill=True) hst = self._returns_cache[self._sid] return (hst.iloc[-1] - hst.iloc[0]) / hst.iloc[0] class BarData(object): """ Holds the event data for all sids for a given dt. This is what is passed as `data` to the `handle_data` function. Note: Many methods are analogues of dictionary because of historical usage of what this replaced as a dictionary subclass. """ def __init__(self, data=None): self._data = data or {} self._contains_override = None def __contains__(self, name): if self._contains_override: if self._contains_override(name): return name in self._data else: return False else: return name in self._data def has_key(self, name): """ DEPRECATED: __contains__ is preferred, but this method is for compatibility with existing algorithms. """ return name in self def __setitem__(self, name, value): self._data[name] = value def __getitem__(self, name): return self._data[name] def __delitem__(self, name): del self._data[name] def __iter__(self): for sid, data in iteritems(self._data): # Allow contains override to filter out sids. if sid in self: if len(data): yield sid def iterkeys(self): # Allow contains override to filter out sids. return (sid for sid in iterkeys(self._data) if sid in self) def keys(self): # Allow contains override to filter out sids. return list(self.iterkeys()) def itervalues(self): return (value for _sid, value in self.iteritems()) def values(self): return list(self.itervalues()) def iteritems(self): return ((sid, value) for sid, value in iteritems(self._data) if sid in self) def items(self): return list(self.iteritems()) def __len__(self): return len(self.keys()) def __repr__(self): return '{0}({1})'.format(self.__class__.__name__, self._data)
vanyh/handkeinzungen-app
refs/heads/master
stats/apps.py
14
from django.apps import AppConfig class StatsConfig(AppConfig): name = 'stats'
HyunsukBaek/etherpad-lite
refs/heads/master
src/node_modules/npm/node_modules/node-gyp/gyp/test/mac/gyptest-rebuild.py
299
#!/usr/bin/env python # Copyright (c) 2012 Google Inc. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """ Verifies that app bundles are rebuilt correctly. """ import TestGyp import sys if sys.platform == 'darwin': test = TestGyp.TestGyp(formats=['ninja', 'make', 'xcode']) CHDIR = 'rebuild' test.run_gyp('test.gyp', chdir=CHDIR) test.build('test.gyp', 'test_app', chdir=CHDIR) # Touch a source file, rebuild, and check that the app target is up-to-date. test.touch('rebuild/main.c') test.build('test.gyp', 'test_app', chdir=CHDIR) test.up_to_date('test.gyp', 'test_app', chdir=CHDIR) # Xcode runs postbuilds on every build, so targets with postbuilds are # never marked as up_to_date. if test.format != 'xcode': # Same for a framework bundle. test.build('test.gyp', 'test_framework_postbuilds', chdir=CHDIR) test.up_to_date('test.gyp', 'test_framework_postbuilds', chdir=CHDIR) # Test that an app bundle with a postbuild that touches the app binary needs # to be built only once. test.build('test.gyp', 'test_app_postbuilds', chdir=CHDIR) test.up_to_date('test.gyp', 'test_app_postbuilds', chdir=CHDIR) test.pass_test()
foo123/sikuli-framework
refs/heads/master
src/log/logger.py
2
""" Copyright (c) 2013, SMART Technologies ULC All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the Copyright holder (SMART Technologies ULC) nor the names of its contributors (Joshua Henn) may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDER (SMART Technologies ULC) "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ import logging import string from log.robotframework import Handler, Formatter class Logger(logging.Logger): """ Main logger class """ formatter = None def __init__(self): logging.Logger.__init__(self, "Logger") # RobotFramework log handler fh = Handler() fh.setFormatter(Formatter()) self.addHandler(fh) # Textfile log handler fh = logging.FileHandler('results/log.txt', mode='w') fh.setFormatter(Formatter()) self.addHandler(fh) def log(self, level, msg, *args, **kwargs): logging.Logger.log(self, level, msg)
coinkeeper/2015-06-22_19-07_digitalcoin
refs/heads/master
contrib/testgen/gen_base58_test_vectors.py
1000
#!/usr/bin/env python ''' Generate valid and invalid base58 address and private key test vectors. Usage: gen_base58_test_vectors.py valid 50 > ../../src/test/data/base58_keys_valid.json gen_base58_test_vectors.py invalid 50 > ../../src/test/data/base58_keys_invalid.json ''' # 2012 Wladimir J. van der Laan # Released under MIT License import os from itertools import islice from base58 import b58encode, b58decode, b58encode_chk, b58decode_chk, b58chars import random from binascii import b2a_hex # key types PUBKEY_ADDRESS = 0 SCRIPT_ADDRESS = 5 PUBKEY_ADDRESS_TEST = 111 SCRIPT_ADDRESS_TEST = 196 PRIVKEY = 128 PRIVKEY_TEST = 239 metadata_keys = ['isPrivkey', 'isTestnet', 'addrType', 'isCompressed'] # templates for valid sequences templates = [ # prefix, payload_size, suffix, metadata # None = N/A ((PUBKEY_ADDRESS,), 20, (), (False, False, 'pubkey', None)), ((SCRIPT_ADDRESS,), 20, (), (False, False, 'script', None)), ((PUBKEY_ADDRESS_TEST,), 20, (), (False, True, 'pubkey', None)), ((SCRIPT_ADDRESS_TEST,), 20, (), (False, True, 'script', None)), ((PRIVKEY,), 32, (), (True, False, None, False)), ((PRIVKEY,), 32, (1,), (True, False, None, True)), ((PRIVKEY_TEST,), 32, (), (True, True, None, False)), ((PRIVKEY_TEST,), 32, (1,), (True, True, None, True)) ] def is_valid(v): '''Check vector v for validity''' result = b58decode_chk(v) if result is None: return False valid = False for template in templates: prefix = str(bytearray(template[0])) suffix = str(bytearray(template[2])) if result.startswith(prefix) and result.endswith(suffix): if (len(result) - len(prefix) - len(suffix)) == template[1]: return True return False def gen_valid_vectors(): '''Generate valid test vectors''' while True: for template in templates: prefix = str(bytearray(template[0])) payload = os.urandom(template[1]) suffix = str(bytearray(template[2])) rv = b58encode_chk(prefix + payload + suffix) assert is_valid(rv) metadata = dict([(x,y) for (x,y) in zip(metadata_keys,template[3]) if y is not None]) yield (rv, b2a_hex(payload), metadata) def gen_invalid_vector(template, corrupt_prefix, randomize_payload_size, corrupt_suffix): '''Generate possibly invalid vector''' if corrupt_prefix: prefix = os.urandom(1) else: prefix = str(bytearray(template[0])) if randomize_payload_size: payload = os.urandom(max(int(random.expovariate(0.5)), 50)) else: payload = os.urandom(template[1]) if corrupt_suffix: suffix = os.urandom(len(template[2])) else: suffix = str(bytearray(template[2])) return b58encode_chk(prefix + payload + suffix) def randbool(p = 0.5): '''Return True with P(p)''' return random.random() < p def gen_invalid_vectors(): '''Generate invalid test vectors''' # start with some manual edge-cases yield "", yield "x", while True: # kinds of invalid vectors: # invalid prefix # invalid payload length # invalid (randomized) suffix (add random data) # corrupt checksum for template in templates: val = gen_invalid_vector(template, randbool(0.2), randbool(0.2), randbool(0.2)) if random.randint(0,10)<1: # line corruption if randbool(): # add random character to end val += random.choice(b58chars) else: # replace random character in the middle n = random.randint(0, len(val)) val = val[0:n] + random.choice(b58chars) + val[n+1:] if not is_valid(val): yield val, if __name__ == '__main__': import sys, json iters = {'valid':gen_valid_vectors, 'invalid':gen_invalid_vectors} try: uiter = iters[sys.argv[1]] except IndexError: uiter = gen_valid_vectors try: count = int(sys.argv[2]) except IndexError: count = 0 data = list(islice(uiter(), count)) json.dump(data, sys.stdout, sort_keys=True, indent=4) sys.stdout.write('\n')
neilhan/tensorflow
refs/heads/master
tensorflow/python/lib/io/python_io.py
18
# Copyright 2015 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """## Data IO (Python Functions) A TFRecords file represents a sequence of (binary) strings. The format is not random access, so it is suitable for streaming large amounts of data but not suitable if fast sharding or other non-sequential access is desired. @@TFRecordWriter @@tf_record_iterator - - - ### TFRecords Format Details A TFRecords file contains a sequence of strings with CRC hashes. Each record has the format uint64 length uint32 masked_crc32_of_length byte data[length] uint32 masked_crc32_of_data and the records are concatenated together to produce the file. The CRC32s are [described here](https://en.wikipedia.org/wiki/Cyclic_redundancy_check), and the mask of a CRC is masked_crc = ((crc >> 15) | (crc << 17)) + 0xa282ead8ul """ from __future__ import absolute_import from __future__ import division from __future__ import print_function # go/tf-wildcard-import # pylint: disable=wildcard-import from tensorflow.python.lib.io.tf_record import * # pylint: enable=wildcard-import from tensorflow.python.util.all_util import make_all __all__ = make_all(__name__)
wearpants/osf.io
refs/heads/develop
website/prereg/views.py
11
"""Back-end code to support the Prereg Challenge initiative Keeping the code together in this file should make it easier to remove the features added to the OSF specifically to support this initiative in the future. Other resources that are a part of the Prereg Challenge: * website/static/js/pages/prereg-landing-page.js * website/static/css/prereg.css """ from flask import request from framework.auth import decorators from framework.utils import iso8601format from website.prereg import utils @decorators.must_be_logged_in def prereg_landing_page(auth, **kwargs): """Landing page for the prereg challenge""" campaign = request.path.strip('/') or 'prereg' registerable_nodes = [ node for node in auth.user.contributor_to if node.has_permission(user=auth.user, permission='admin') ] has_projects = bool(registerable_nodes) has_draft_registrations = bool(utils.drafts_for_user(auth.user, campaign).count()) return { 'has_draft_registrations': has_draft_registrations, 'has_projects': has_projects, 'campaign_long': utils.PREREG_CAMPAIGNS[campaign], 'campaign_short': campaign } @decorators.must_be_logged_in def prereg_draft_registrations(auth, **kwargs): """API endpoint; returns prereg draft registrations the user can resume""" campaign = kwargs.get('campaign', 'prereg') drafts = utils.drafts_for_user(auth.user, campaign) return { 'draftRegistrations': [ { 'dateUpdated': iso8601format(draft.datetime_updated), 'dateInitiated': iso8601format(draft.datetime_initiated), 'node': { 'title': draft.branched_from.title, }, 'initiator': { 'name': draft.initiator.fullname, }, 'url': draft.branched_from.web_url_for( 'edit_draft_registration_page', draft_id=draft._id, ), } for draft in drafts ], }
linea-it/qlf
refs/heads/master
backend/framework/qlf/dashboard/bokeh/globalfiber/main.py
2
from bokeh.plotting import figure from bokeh.layouts import row, column from bokeh.models import HoverTool, ColumnDataSource, Range1d from qlf_models import QLFModels from dashboard.bokeh.plots.descriptors.title import Title import numpy as np import logging from bokeh.resources import CDN from bokeh.embed import file_html import os from dashboard.models import Job, Process, Fibermap spectro_data = os.environ.get('DESI_SPECTRO_DATA') logger = logging.getLogger(__name__) class GlobalFiber: def __init__(self, process_id, arm): self.selected_process_id = process_id self.selected_arm = arm def data_source(self, fmap): """ Creating data source for plots """ data_model = { 'goodfiber': [], 'status': [], 'color': [], 'cam': [], 'OBJ_TYPE': [], 'ra': [], 'dec': [], } process_id = self.selected_process_id joblist = [entry.camera.camera for entry in Job.objects.filter( process_id=process_id)] ra_tile = fmap.fiber_ra dec_tile = fmap.fiber_dec otype_tile = fmap.objtype y = [] color = [] status = [] cam_inst = [] for spec in list(range(10)): cam = self.selected_arm+str(spec) if cam in joblist: mergedqa = QLFModels().get_output( self.selected_process_id, cam) countbins = mergedqa['TASKS']['CHECK_FIBERS']['METRICS']['GOOD_FIBERS'] y = y + countbins color = color + ['green' if idx == 1 else 'red' for idx in countbins] status = status + ['GOOD' if idx == 1 else 'BAD' for idx in countbins] else: y = y + 500*[''] color = color + ['lightgray']*500 status = status + ['']*500 cam_inst = cam_inst + [cam]*500 data_model['goodfiber'] = y data_model['color'] = color data_model['status'] = status data_model['cam'] = cam_inst data_model['OBJ_TYPE'] = otype_tile data_model['ra'] = ra_tile data_model['dec'] = dec_tile source = ColumnDataSource(data=data_model) return source def wedge_plot(self, wedge_arm, fmap, common_source=None): ra_center = fmap.exposure.telra dec_center = fmap.exposure.teldec fiber_tooltip = """ <div> <div> <span style="font-size: 12px; font-weight: bold; color: #303030;">FIBER STATUS: </span> <span style="font-size: 13px; color: #515151">@status</span> </div> <div> <span style="font-size: 12px; font-weight: bold; color: #303030;">RA: </span> <span style="font-size: 13px; color: #515151;">@ra</span> </div> <div> <span style="font-size: 12px; font-weight: bold; color: #303030;">DEC: </span> <span style="font-size: 13px; color: #515151;">@dec</span> </div> <div> <span style="font-size: 12px; font-weight: bold; color: #303030;">Obj Type: </span> <span style="font-size: 13px; color: #515151;">@OBJ_TYPE</span> </div> <div> <span style="font-size: 12px; font-weight: bold; color: #303030;">CAM: </span> <span style="font-size: 13px; color: #515151;">@cam_</span> </div> """.replace('@status', '@status').replace('@cam_', '@cam') hover = HoverTool(tooltips=fiber_tooltip) source = common_source radius = 0.017 radius_hover = 0.018 plot_space=-0.1 xrange = Range1d(start=max(source.data['ra'])-plot_space, end=min(source.data['ra'])+plot_space) yrange = Range1d(start=max(source.data['dec'])-plot_space, end=min(source.data['dec'])+plot_space) p = figure(title='FIBERS - ARM %s' % (wedge_arm), x_axis_label='RA', y_axis_label='DEC', tools=[hover,"box_zoom,pan,wheel_zoom,reset,lasso_select,crosshair"], active_drag="box_zoom", x_range=xrange, y_range=yrange, sizing_mode='scale_width') p.title.align = 'center' p.circle('ra', 'dec', source=source, name="data", radius=radius, fill_color={'field': 'color'}, line_color='black', line_width=0.4, hover_line_color='red') p.circle('ra', 'dec', source=source, name="data", radius=radius_hover, hover_fill_color={'field': 'color'}, fill_color=None, line_color=None, line_width=3, hover_line_color='red') return p def load_qa(self): process_id = self.selected_process_id process = Process.objects.get(pk=process_id) exposure = process.exposure fmap = Fibermap.objects.filter(exposure=exposure)[0] src = self.data_source(fmap) p = self.wedge_plot(self.selected_arm, fmap, common_source=src) info_col = Title().write_description('globalfiber') layout = column([info_col, p], sizing_mode='scale_width') return file_html(layout, CDN, "Global Fiber") if __name__ == '__main__': print('debbuging instance')
xwolf12/django
refs/heads/master
tests/utils_tests/test_os_utils.py
482
import os import unittest from django.core.exceptions import SuspiciousFileOperation from django.utils._os import safe_join class SafeJoinTests(unittest.TestCase): def test_base_path_ends_with_sep(self): drive, path = os.path.splitdrive(safe_join("/abc/", "abc")) self.assertEqual( path, "{0}abc{0}abc".format(os.path.sep) ) def test_root_path(self): drive, path = os.path.splitdrive(safe_join("/", "path")) self.assertEqual( path, "{}path".format(os.path.sep), ) drive, path = os.path.splitdrive(safe_join("/", "")) self.assertEqual( path, os.path.sep, ) def test_parent_path(self): with self.assertRaises(SuspiciousFileOperation): safe_join("/abc/", "../def")
jswanljung/iris
refs/heads/master
lib/iris/tests/unit/quickplot/test_pcolor.py
11
# (C) British Crown Copyright 2014 - 2016, Met Office # # This file is part of Iris. # # Iris is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the # Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # Iris is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with Iris. If not, see <http://www.gnu.org/licenses/>. """Unit tests for the `iris.quickplot.pcolor` function.""" from __future__ import (absolute_import, division, print_function) from six.moves import (filter, input, map, range, zip) # noqa # Import iris.tests first so that some things can be initialised before # importing anything else. import iris.tests as tests import numpy as np from iris.tests.stock import simple_2d from iris.tests.unit.plot import TestGraphicStringCoord, MixinCoords if tests.MPL_AVAILABLE: import iris.quickplot as qplt @tests.skip_plot class TestStringCoordPlot(TestGraphicStringCoord): def test_yaxis_labels(self): qplt.pcolor(self.cube, coords=('bar', 'str_coord')) self.assertBoundsTickLabels('yaxis') def test_xaxis_labels(self): qplt.pcolor(self.cube, coords=('str_coord', 'bar')) self.assertBoundsTickLabels('xaxis') @tests.skip_plot class TestCoords(tests.IrisTest, MixinCoords): def setUp(self): # We have a 2d cube with dimensionality (bar: 3; foo: 4) self.cube = simple_2d(with_bounds=True) coord = self.cube.coord('foo') self.foo = coord.contiguous_bounds() self.foo_index = np.arange(coord.points.size + 1) coord = self.cube.coord('bar') self.bar = coord.contiguous_bounds() self.bar_index = np.arange(coord.points.size + 1) self.data = self.cube.data self.dataT = self.data.T self.mpl_patch = self.patch('matplotlib.pyplot.pcolor', return_value=None) self.draw_func = qplt.pcolor if __name__ == "__main__": tests.main()
chriskmanx/qmole
refs/heads/master
QMOLEDEV/vte-0.24.1/python/vte-demo.py
7
#!/usr/bin/python import sys import string import getopt import gtk import vte def selected_cb(terminal, column, row, cb_data): if (row == 15): if (column < 40): return 1 return 0 def restore_cb(terminal): (text, attrs) = terminal.get_text(selected_cb, 1) print "A portion of the text at restore-time is:" print text def child_exited_cb(terminal): gtk.main_quit() if __name__ == '__main__': child_pid = -1; # Defaults. audible = 0 background = None blink = 0 command = None emulation = "xterm" font = "fixed 12" scrollback = 100 transparent = 0 visible = 0 # Let the user override them. (shorts, longs) = getopt.getopt(sys.argv[1:], "B:Tabc:f:n:t:v", ["background", "transparent", "audible", "blink", "command=", "font=", "scrollback=", "terminal=", "visible"]) for argpair in (shorts + longs): if ((argpair[0] == '-B') or (argpair[0] == '--background')): print "Setting background image to `" + argpair[1] + "'." background = argpair[1] if ((argpair[0] == '-T') or (argpair[0] == '--transparent')): print "Setting transparency." transparent = not transparent if ((argpair[0] == '-a') or (argpair[0] == '--audible')): print "Setting audible bell." audible = not audible if ((argpair[0] == '-b') or (argpair[0] == '--blink')): print "Setting blinking cursor." blink = not blink if ((argpair[0] == '-c') or (argpair[0] == '--command')): print "Running command `" + argpair[1] + "'." command = argpair[1] if ((argpair[0] == '-f') or (argpair[0] == '--font')): print "Setting font to `" + argpair[1] + "'." font = argpair[1] if ((argpair[0] == '-n') or (argpair[0] == '--scrollback')): scrollback = string.atoi(argpair[1]) if (scrollback == 0): scrollback = 100 else: print "Setting scrollback size to `" + str(scrollback) + "'." if ((argpair[0] == '-t') or (argpair[0] == '--terminal')): print "Setting terminal type to `" + argpair[1] + "'." emulation = argpair[1] if ((argpair[0] == '-v') or (argpair[0] == '--visible')): print "Setting visible bell." visible = not visible window = gtk.Window() terminal = vte.Terminal() if (background): terminal.set_background_image(background) if (transparent): terminal.set_background_transparent(gtk.TRUE) terminal.set_cursor_blinks(blink) terminal.set_emulation(emulation) terminal.set_font_from_string(font) terminal.set_scrollback_lines(scrollback) terminal.set_audible_bell(audible) terminal.set_visible_bell(visible) terminal.connect("child-exited", child_exited_cb) terminal.connect("restore-window", restore_cb) if (command): # Start up the specified command. child_pid = terminal.fork_command(command) else: # Start up the default command, the user's shell. child_pid = terminal.fork_command() terminal.show() scrollbar = gtk.VScrollbar() scrollbar.set_adjustment(terminal.get_adjustment()) box = gtk.HBox() box.pack_start(terminal) box.pack_start(scrollbar) window.add(box) window.show_all() gtk.main()
renatopp/liac
refs/heads/master
samples/models/samples_kernelpca.py
1
# ============================================================================= # Federal University of Rio Grande do Sul (UFRGS) # Connectionist Artificial Intelligence Laboratory (LIAC) # Renato de Pontes Pereira - rppereira@inf.ufrgs.br # ============================================================================= # Copyright (c) 2011 Renato de Pontes Pereira, renato.ppontes at gmail dot com # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # ============================================================================= import sys import os sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..')) import liac from liac import plot data = liac.dataset.load('iris') targets = data.iloc[:, -1] classes = targets.unique() data = data.iloc[:, 0:-1] kpca = liac.models.KernelPCA(2, 'linear') kpca.fit(data) transformed_data = kpca.transform(data) for i, label in enumerate(classes): idx = targets == label d = transformed_data[idx] plot.scatter(d[:, 0], d[:, 1], color=liac.random.make_color(i)) plot.show()
jlegendary/nupic
refs/heads/master
tests/swarming/nupic/swarming/experiments/dummyV2/description.py
8
# ---------------------------------------------------------------------- # Numenta Platform for Intelligent Computing (NuPIC) # Copyright (C) 2013, Numenta, Inc. Unless you have an agreement # with Numenta, Inc., for a separate license for this software code, the # following terms and conditions apply: # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License version 3 as # published by the Free Software Foundation. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. # See the GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see http://www.gnu.org/licenses. # # http://numenta.org/licenses/ # ---------------------------------------------------------------------- """ Template file used by the OPF Experiment Generator to generate the actual description.py file by replacing $XXXXXXXX tokens with desired values. This description.py file was generated by: '/Users/ronmarianetti/nupic/eng/lib/python2.6/site-packages/nupic/frameworks/opf/expGenerator/ExpGenerator.py' """ from nupic.frameworks.opf.expdescriptionapi import ExperimentDescriptionAPI from nupic.frameworks.opf.expdescriptionhelpers import ( updateConfigFromSubConfig, applyValueGettersToContainer, DeferredDictLookup) from nupic.frameworks.opf.clamodelcallbacks import * from nupic.frameworks.opf.metrics import MetricSpec from nupic.frameworks.opf.opfutils import (InferenceType, InferenceElement) from nupic.support import aggregationDivide from nupic.frameworks.opf.opftaskdriver import ( IterationPhaseSpecLearnOnly, IterationPhaseSpecInferOnly, IterationPhaseSpecLearnAndInfer) # Model Configuration Dictionary: # # Define the model parameters and adjust for any modifications if imported # from a sub-experiment. # # These fields might be modified by a sub-experiment; this dict is passed # between the sub-experiment and base experiment # # # NOTE: Use of DEFERRED VALUE-GETTERs: dictionary fields and list elements # within the config dictionary may be assigned futures derived from the # ValueGetterBase class, such as DeferredDictLookup. # This facility is particularly handy for enabling substitution of values in # the config dictionary from other values in the config dictionary, which is # needed by permutation.py-based experiments. These values will be resolved # during the call to applyValueGettersToContainer(), # which we call after the base experiment's config dictionary is updated from # the sub-experiment. See ValueGetterBase and # DeferredDictLookup for more details about value-getters. # # For each custom encoder parameter to be exposed to the sub-experiment/ # permutation overrides, define a variable in this section, using key names # beginning with a single underscore character to avoid collisions with # pre-defined keys (e.g., _dsEncoderFieldName2_N). # # Example: # config = dict( # _dsEncoderFieldName2_N = 70, # _dsEncoderFieldName2_W = 5, # dsEncoderSchema = [ # base=dict( # fieldname='Name2', type='ScalarEncoder', # name='Name2', minval=0, maxval=270, clipInput=True, # n=DeferredDictLookup('_dsEncoderFieldName2_N'), # w=DeferredDictLookup('_dsEncoderFieldName2_W')), # ], # ) # updateConfigFromSubConfig(config) # applyValueGettersToContainer(config) config = { # Type of model that the rest of these parameters apply to. 'model': "CLA", # Version that specifies the format of the config. 'version': 1, # Intermediate variables used to compute fields in modelParams and also # referenced from the control section. 'aggregationInfo': { 'days': 0, 'fields': [ (u'timestamp', 'first'), (u'gym', 'first'), (u'consumption', 'mean'), (u'address', 'first')], 'hours': 0, 'microseconds': 0, 'milliseconds': 0, 'minutes': 0, 'months': 0, 'seconds': 0, 'weeks': 0, 'years': 0}, 'predictAheadTime': None, # Model parameter dictionary. 'modelParams': { # The type of inference that this model will perform 'inferenceType': 'TemporalNextStep', 'sensorParams': { # Sensor diagnostic output verbosity control; # if > 0: sensor region will print out on screen what it's sensing # at each step 0: silent; >=1: some info; >=2: more info; # >=3: even more info (see compute() in py/regions/RecordSensor.py) 'verbosity' : 0, # Example: # dsEncoderSchema = [ # DeferredDictLookup('__field_name_encoder'), # ], # # (value generated from DS_ENCODER_SCHEMA) 'encoders': { 'address': { 'fieldname': u'address', 'n': 300, 'name': u'address', 'type': 'SDRCategoryEncoder', 'w': 21}, 'consumption': { 'clipInput': True, 'fieldname': u'consumption', 'maxval': 200, 'minval': 0, 'n': 1500, 'name': u'consumption', 'type': 'ScalarEncoder', 'w': 21}, 'gym': { 'fieldname': u'gym', 'n': 600, 'name': u'gym', 'type': 'SDRCategoryEncoder', 'w': 21}, 'timestamp_dayOfWeek': { 'dayOfWeek': (7, 3), 'fieldname': u'timestamp', 'name': u'timestamp_dayOfWeek', 'type': 'DateEncoder'}, 'timestamp_timeOfDay': { 'fieldname': u'timestamp', 'name': u'timestamp_timeOfDay', 'timeOfDay': (7, 8), 'type': 'DateEncoder'}}, # A dictionary specifying the period for automatically-generated # resets from a RecordSensor; # # None = disable automatically-generated resets (also disabled if # all of the specified values evaluate to 0). # Valid keys is the desired combination of the following: # days, hours, minutes, seconds, milliseconds, microseconds, weeks # # Example for 1.5 days: sensorAutoReset = dict(days=1,hours=12), # # (value generated from SENSOR_AUTO_RESET) 'sensorAutoReset' : None, }, 'spEnable': True, 'spParams': { # SP diagnostic output verbosity control; # 0: silent; >=1: some info; >=2: more info; 'spVerbosity' : 0, 'globalInhibition': 1, # Number of cell columns in the cortical region (same number for # SP and TP) # (see also tpNCellsPerCol) 'columnCount': 2048, 'inputWidth': 0, # SP inhibition control (absolute value); # Maximum number of active columns in the SP region's output (when # there are more, the weaker ones are suppressed) 'numActiveColumnsPerInhArea': 40, 'seed': 1956, # potentialPct # What percent of the columns's receptive field is available # for potential synapses. At initialization time, we will # choose potentialPct * (2*potentialRadius+1)^2 'potentialPct': 0.5, # The default connected threshold. Any synapse whose # permanence value is above the connected threshold is # a "connected synapse", meaning it can contribute to the # cell's firing. Typical value is 0.10. Cells whose activity # level before inhibition falls below minDutyCycleBeforeInh # will have their own internal synPermConnectedCell # threshold set below this default value. # (This concept applies to both SP and TP and so 'cells' # is correct here as opposed to 'columns') 'synPermConnected': 0.1, 'synPermActiveInc': 0.1, 'synPermInactiveDec': 0.01, }, # Controls whether TP is enabled or disabled; # TP is necessary for making temporal predictions, such as predicting # the next inputs. Without TP, the model is only capable of # reconstructing missing sensor inputs (via SP). 'tpEnable' : True, 'tpParams': { # TP diagnostic output verbosity control; # 0: silent; [1..6]: increasing levels of verbosity # (see verbosity in nupic/trunk/py/nupic/research/TP.py and TP10X*.py) 'verbosity': 0, # Number of cell columns in the cortical region (same number for # SP and TP) # (see also tpNCellsPerCol) 'columnCount': 2048, # The number of cells (i.e., states), allocated per column. 'cellsPerColumn': 32, 'inputWidth': 2048, 'seed': 1960, # Temporal Pooler implementation selector (see _getTPClass in # CLARegion.py). 'temporalImp': 'cpp', # New Synapse formation count # NOTE: If None, use spNumActivePerInhArea # # TODO: need better explanation 'newSynapseCount': 15, # Maximum number of synapses per segment # > 0 for fixed-size CLA # -1 for non-fixed-size CLA # # TODO: for Ron: once the appropriate value is placed in TP # constructor, see if we should eliminate this parameter from # description.py. 'maxSynapsesPerSegment': 32, # Maximum number of segments per cell # > 0 for fixed-size CLA # -1 for non-fixed-size CLA # # TODO: for Ron: once the appropriate value is placed in TP # constructor, see if we should eliminate this parameter from # description.py. 'maxSegmentsPerCell': 128, # Initial Permanence # TODO: need better explanation 'initialPerm': 0.21, # Permanence Increment 'permanenceInc': 0.1, # Permanence Decrement # If set to None, will automatically default to tpPermanenceInc # value. 'permanenceDec' : 0.1, 'globalDecay': 0.0, 'maxAge': 0, # Minimum number of active synapses for a segment to be considered # during search for the best-matching segments. # None=use default # Replaces: tpMinThreshold 'minThreshold': 12, # Segment activation threshold. # A segment is active if it has >= tpSegmentActivationThreshold # connected synapses that are active due to infActiveState # None=use default # Replaces: tpActivationThreshold 'activationThreshold': 16, 'outputType': 'normal', # "Pay Attention Mode" length. This tells the TP how many new # elements to append to the end of a learned sequence at a time. # Smaller values are better for datasets with short sequences, # higher values are better for datasets with long sequences. 'pamLength': 1, }, 'clParams': { 'regionName' : 'CLAClassifierRegion', # Classifier diagnostic output verbosity control; # 0: silent; [1..6]: increasing levels of verbosity 'clVerbosity' : 0, # This controls how fast the classifier learns/forgets. Higher values # make it adapt faster and forget older patterns faster. 'alpha': 0.001, # This is set after the call to updateConfigFromSubConfig and is # computed from the aggregationInfo and predictAheadTime. 'steps': '1', }, 'trainSPNetOnlyIfRequested': False, }, } # end of config dictionary # Adjust base config dictionary for any modifications if imported from a # sub-experiment updateConfigFromSubConfig(config) # Compute predictionSteps based on the predictAheadTime and the aggregation # period, which may be permuted over. if config['predictAheadTime'] is not None: predictionSteps = int(round(aggregationDivide( config['predictAheadTime'], config['aggregationInfo']))) assert (predictionSteps >= 1) config['modelParams']['clParams']['steps'] = str(predictionSteps) # Adjust config by applying ValueGetterBase-derived # futures. NOTE: this MUST be called after updateConfigFromSubConfig() in order # to support value-getter-based substitutions from the sub-experiment (if any) applyValueGettersToContainer(config) control = { # The environment that the current model is being run in "environment": 'nupic', # Input stream specification per py/nupicengine/cluster/database/StreamDef.json. # 'dataset' : {u'info': u'test_NoProviders', u'streams': [ { u'columns': [u'*'], u'info': "test data", u'source': "file://swarming/test_data.csv"}], u'version': 1}, # Iteration count: maximum number of iterations. Each iteration corresponds # to one record from the (possibly aggregated) dataset. The task is # terminated when either number of iterations reaches iterationCount or # all records in the (possibly aggregated) database have been processed, # whichever occurs first. # # iterationCount of -1 = iterate over the entire dataset #'iterationCount' : ITERATION_COUNT, # Metrics: A list of MetricSpecs that instantiate the metrics that are # computed for this experiment 'metrics':[ MetricSpec(field=u'consumption',inferenceElement=InferenceElement.prediction, metric='rmse'), ], # Logged Metrics: A sequence of regular expressions that specify which of # the metrics from the Inference Specifications section MUST be logged for # every prediction. The regex's correspond to the automatically generated # metric labels. This is similar to the way the optimization metric is # specified in permutations.py. } descriptionInterface = ExperimentDescriptionAPI(modelConfig=config, control=control)
aperigault/ansible
refs/heads/devel
lib/ansible/modules/cloud/ovirt/ovirt_template.py
15
#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright (c) 2016 Red Hat, Inc. # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ['preview'], 'supported_by': 'community'} DOCUMENTATION = ''' --- module: ovirt_template short_description: Module to manage virtual machine templates in oVirt/RHV version_added: "2.3" author: "Ondra Machacek (@machacekondra)" description: - "Module to manage virtual machine templates in oVirt/RHV." options: name: description: - "Name of the template to manage." id: description: - "ID of the template to be registered." version_added: "2.4" state: description: - "Should the template be present/absent/exported/imported/registered. When C(state) is I(registered) and the unregistered template's name belongs to an already registered in engine template in the same DC then we fail to register the unregistered template." choices: ['present', 'absent', 'exported', 'imported', 'registered'] default: present vm: description: - "Name of the VM, which will be used to create template." description: description: - "Description of the template." cpu_profile: description: - "CPU profile to be set to template." cluster: description: - "Name of the cluster, where template should be created/imported." allow_partial_import: description: - "Boolean indication whether to allow partial registration of a template when C(state) is registered." type: bool version_added: "2.4" vnic_profile_mappings: description: - "Mapper which maps an external virtual NIC profile to one that exists in the engine when C(state) is registered. vnic_profile is described by the following dictionary:" suboptions: source_network_name: description: - The network name of the source network. source_profile_name: description: - The profile name related to the source network. target_profile_id: description: - The id of the target profile id to be mapped to in the engine. version_added: "2.5" cluster_mappings: description: - "Mapper which maps cluster name between Template's OVF and the destination cluster this Template should be registered to, relevant when C(state) is registered. Cluster mapping is described by the following dictionary:" suboptions: source_name: description: - The name of the source cluster. dest_name: description: - The name of the destination cluster. version_added: "2.5" role_mappings: description: - "Mapper which maps role name between Template's OVF and the destination role this Template should be registered to, relevant when C(state) is registered. Role mapping is described by the following dictionary:" suboptions: source_name: description: - The name of the source role. dest_name: description: - The name of the destination role. version_added: "2.5" domain_mappings: description: - "Mapper which maps aaa domain name between Template's OVF and the destination aaa domain this Template should be registered to, relevant when C(state) is registered. The aaa domain mapping is described by the following dictionary:" suboptions: source_name: description: - The name of the source aaa domain. dest_name: description: - The name of the destination aaa domain. version_added: "2.5" exclusive: description: - "When C(state) is I(exported) this parameter indicates if the existing templates with the same name should be overwritten." type: bool export_domain: description: - "When C(state) is I(exported) or I(imported) this parameter specifies the name of the export storage domain." image_provider: description: - "When C(state) is I(imported) this parameter specifies the name of the image provider to be used." image_disk: description: - "When C(state) is I(imported) and C(image_provider) is used this parameter specifies the name of disk to be imported as template." aliases: ['glance_image_disk_name'] io_threads: description: - "Number of IO threads used by virtual machine. I(0) means IO threading disabled." version_added: "2.7" template_image_disk_name: description: - "When C(state) is I(imported) and C(image_provider) is used this parameter specifies the new name for imported disk, if omitted then I(image_disk) name is used by default. This parameter is used only in case of importing disk image from Glance domain." version_added: "2.4" storage_domain: description: - "When C(state) is I(imported) this parameter specifies the name of the destination data storage domain. When C(state) is I(registered) this parameter specifies the name of the data storage domain of the unregistered template." clone_permissions: description: - "If I(True) then the permissions of the VM (only the direct ones, not the inherited ones) will be copied to the created template." - "This parameter is used only when C(state) I(present)." type: bool default: False seal: description: - "'Sealing' is an operation that erases all machine-specific configurations from a filesystem: This includes SSH keys, UDEV rules, MAC addresses, system ID, hostname, etc. If I(true) subsequent virtual machines made from this template will avoid configuration inheritance." - "This parameter is used only when C(state) I(present)." default: False type: bool version_added: "2.5" operating_system: description: - Operating system of the template. - Default value is set by oVirt/RHV engine. - "Possible values are: debian_7, freebsd, freebsdx64, other, other_linux, other_linux_ppc64, other_ppc64, rhel_3, rhel_4, rhel_4x64, rhel_5, rhel_5x64, rhel_6, rhel_6x64, rhel_6_ppc64, rhel_7x64, rhel_7_ppc64, sles_11, sles_11_ppc64, ubuntu_12_04, ubuntu_12_10, ubuntu_13_04, ubuntu_13_10, ubuntu_14_04, ubuntu_14_04_ppc64, windows_10, windows_10x64, windows_2003, windows_2003x64, windows_2008, windows_2008x64, windows_2008r2x64, windows_2008R2x64, windows_2012x64, windows_2012R2x64, windows_7, windows_7x64, windows_8, windows_8x64, windows_xp" version_added: "2.6" memory: description: - Amount of memory of the template. Prefix uses IEC 60027-2 standard (for example 1GiB, 1024MiB). version_added: "2.6" memory_guaranteed: description: - Amount of minimal guaranteed memory of the template. Prefix uses IEC 60027-2 standard (for example 1GiB, 1024MiB). - C(memory_guaranteed) parameter can't be lower than C(memory) parameter. version_added: "2.6" memory_max: description: - Upper bound of template memory up to which memory hot-plug can be performed. Prefix uses IEC 60027-2 standard (for example 1GiB, 1024MiB). version_added: "2.6" version: description: - "C(name) - The name of this version." - "C(number) - The index of this version in the versions hierarchy of the template. Used for editing of sub template." version_added: "2.8" clone_name: description: - Name for importing Template from storage domain. - If not defined, C(name) will be used. version_added: "2.8" usb_support: description: - "I(True) enable USB support, I(False) to disable it. By default is chosen by oVirt/RHV engine." type: bool version_added: "2.9" timezone: description: - Sets time zone offset of the guest hardware clock. - For example C(Etc/GMT) version_added: "2.9" sso: description: - "I(True) enable Single Sign On by Guest Agent, I(False) to disable it. By default is chosen by oVirt/RHV engine." type: bool version_added: "2.9" soundcard_enabled: description: - "If I(true), the sound card is added to the virtual machine." type: bool version_added: "2.9" smartcard_enabled: description: - "If I(true), use smart card authentication." type: bool version_added: "2.9" cloud_init: description: - Dictionary with values for Unix-like Virtual Machine initialization using cloud init. suboptions: host_name: description: - Hostname to be set to Virtual Machine when deployed. timezone: description: - Timezone to be set to Virtual Machine when deployed. user_name: description: - Username to be used to set password to Virtual Machine when deployed. root_password: description: - Password to be set for user specified by C(user_name) parameter. authorized_ssh_keys: description: - Use this SSH keys to login to Virtual Machine. regenerate_ssh_keys: description: - If I(True) SSH keys will be regenerated on Virtual Machine. type: bool custom_script: description: - Cloud-init script which will be executed on Virtual Machine when deployed. - This is appended to the end of the cloud-init script generated by any other options. dns_servers: description: - DNS servers to be configured on Virtual Machine. dns_search: description: - DNS search domains to be configured on Virtual Machine. nic_boot_protocol: description: - Set boot protocol of the network interface of Virtual Machine. choices: ['none', 'dhcp', 'static'] nic_ip_address: description: - If boot protocol is static, set this IP address to network interface of Virtual Machine. nic_netmask: description: - If boot protocol is static, set this netmask to network interface of Virtual Machine. nic_gateway: description: - If boot protocol is static, set this gateway to network interface of Virtual Machine. nic_name: description: - Set name to network interface of Virtual Machine. nic_on_boot: description: - If I(True) network interface will be set to start on boot. type: bool version_added: "2.9" cloud_init_nics: description: - List of dictionaries representing network interfaces to be setup by cloud init. - This option is used, when user needs to setup more network interfaces via cloud init. - If one network interface is enough, user should use C(cloud_init) I(nic_*) parameters. C(cloud_init) I(nic_*) parameters are merged with C(cloud_init_nics) parameters. suboptions: nic_boot_protocol: description: - Set boot protocol of the network interface of Virtual Machine. Can be one of C(none), C(dhcp) or C(static). nic_ip_address: description: - If boot protocol is static, set this IP address to network interface of Virtual Machine. nic_netmask: description: - If boot protocol is static, set this netmask to network interface of Virtual Machine. nic_gateway: description: - If boot protocol is static, set this gateway to network interface of Virtual Machine. nic_name: description: - Set name to network interface of Virtual Machine. nic_on_boot: description: - If I(True) network interface will be set to start on boot. type: bool version_added: "2.9" ballooning_enabled: description: - "If I(true), use memory ballooning." - "Memory balloon is a guest device, which may be used to re-distribute / reclaim the host memory based on VM needs in a dynamic way. In this way it's possible to create memory over commitment states." type: bool version_added: "2.9" nics: description: - List of NICs, which should be attached to Virtual Machine. NIC is described by following dictionary. suboptions: name: description: - Name of the NIC. profile_name: description: - Profile name where NIC should be attached. interface: description: - Type of the network interface. choices: ['virtio', 'e1000', 'rtl8139'] default: 'virtio' mac_address: description: - Custom MAC address of the network interface, by default it's obtained from MAC pool. version_added: "2.9" sysprep: description: - Dictionary with values for Windows Virtual Machine initialization using sysprep. suboptions: host_name: description: - Hostname to be set to Virtual Machine when deployed. active_directory_ou: description: - Active Directory Organizational Unit, to be used for login of user. org_name: description: - Organization name to be set to Windows Virtual Machine. domain: description: - Domain to be set to Windows Virtual Machine. timezone: description: - Timezone to be set to Windows Virtual Machine. ui_language: description: - UI language of the Windows Virtual Machine. system_locale: description: - System localization of the Windows Virtual Machine. input_locale: description: - Input localization of the Windows Virtual Machine. windows_license_key: description: - License key to be set to Windows Virtual Machine. user_name: description: - Username to be used for set password to Windows Virtual Machine. root_password: description: - Password to be set for username to Windows Virtual Machine. version_added: "2.9" extends_documentation_fragment: ovirt ''' EXAMPLES = ''' # Examples don't contain auth parameter for simplicity, # look at ovirt_auth module to see how to reuse authentication: # Create template from vm - ovirt_template: cluster: Default name: mytemplate vm: rhel7 cpu_profile: Default description: Test # Import template - ovirt_template: state: imported name: mytemplate export_domain: myexport storage_domain: mystorage cluster: mycluster # Remove template - ovirt_template: state: absent name: mytemplate # Change Template Name - ovirt_template: id: 00000000-0000-0000-0000-000000000000 name: "new_template_name" # Register template - ovirt_template: state: registered storage_domain: mystorage cluster: mycluster name: mytemplate # Register template using id - ovirt_template: state: registered storage_domain: mystorage cluster: mycluster id: 1111-1111-1111-1111 # Register template, allowing partial import - ovirt_template: state: registered storage_domain: mystorage allow_partial_import: "True" cluster: mycluster id: 1111-1111-1111-1111 # Register template with vnic profile mappings - ovirt_template: state: registered storage_domain: mystorage cluster: mycluster id: 1111-1111-1111-1111 vnic_profile_mappings: - source_network_name: mynetwork source_profile_name: mynetwork target_profile_id: 3333-3333-3333-3333 - source_network_name: mynetwork2 source_profile_name: mynetwork2 target_profile_id: 4444-4444-4444-4444 # Register template with mapping - ovirt_template: state: registered storage_domain: mystorage cluster: mycluster id: 1111-1111-1111-1111 role_mappings: - source_name: Role_A dest_name: Role_B domain_mappings: - source_name: Domain_A dest_name: Domain_B cluster_mappings: - source_name: cluster_A dest_name: cluster_B # Import image from Glance s a template - ovirt_template: state: imported name: mytemplate image_disk: "centos7" template_image_disk_name: centos7_from_glance image_provider: "glance_domain" storage_domain: mystorage cluster: mycluster # Edit template subeversion - ovirt_template: cluster: mycluster name: mytemplate vm: rhel7 version: number: 2 name: subversion # Create new template subeversion - ovirt_template: cluster: mycluster name: mytemplate vm: rhel7 version: name: subversion - name: Template with cloud init ovirt_template: name: mytemplate cluster: Default memory: 1GiB cloud_init: nic_boot_protocol: static nic_ip_address: 10.34.60.86 nic_netmask: 255.255.252.0 nic_gateway: 10.34.63.254 nic_name: eth1 nic_on_boot: true host_name: example.com custom_script: | write_files: - content: | Hello, world! path: /tmp/greeting.txt permissions: '0644' user_name: root root_password: super_password - name: Template with cloud init, with multiple network interfaces ovirt_template: name: mytemplate cluster: mycluster cloud_init_nics: - nic_name: eth0 nic_boot_protocol: dhcp nic_on_boot: true - nic_name: eth1 nic_boot_protocol: static nic_ip_address: 10.34.60.86 nic_netmask: 255.255.252.0 nic_gateway: 10.34.63.254 nic_on_boot: true - name: Template with timezone and nic ovirt_template: cluster: MyCluster name: mytemplate timezone: America/Godthab memory_max: 2Gib nics: - name: nic1 - name: Template with sysprep ovirt_vm: name: windows2012R2_AD cluster: Default memory: 3GiB sysprep: host_name: windowsad.example.com user_name: Administrator root_password: SuperPassword123 ''' RETURN = ''' id: description: ID of the template which is managed returned: On success if template is found. type: str sample: 7de90f31-222c-436c-a1ca-7e655bd5b60c template: description: "Dictionary of all the template attributes. Template attributes can be found on your oVirt/RHV instance at following url: http://ovirt.github.io/ovirt-engine-api-model/master/#types/template." returned: On success if template is found. type: dict ''' import time import traceback try: import ovirtsdk4.types as otypes except ImportError: pass from ansible.module_utils.basic import AnsibleModule from ansible.module_utils.ovirt import ( BaseModule, check_sdk, convert_to_bytes, create_connection, equal, get_dict_of_struct, get_link_name, get_id_by_name, ovirt_full_argument_spec, search_by_attributes, search_by_name, ) class TemplatesModule(BaseModule): def __init__(self, *args, **kwargs): super(TemplatesModule, self).__init__(*args, **kwargs) self._initialization = None def build_entity(self): return otypes.Template( id=self._module.params['id'], name=self._module.params['name'], cluster=otypes.Cluster( name=self._module.params['cluster'] ) if self._module.params['cluster'] else None, vm=otypes.Vm( name=self._module.params['vm'] ) if self._module.params['vm'] else None, description=self._module.params['description'], cpu_profile=otypes.CpuProfile( id=search_by_name( self._connection.system_service().cpu_profiles_service(), self._module.params['cpu_profile'], ).id ) if self._module.params['cpu_profile'] else None, display=otypes.Display( smartcard_enabled=self.param('smartcard_enabled') ) if self.param('smartcard_enabled') is not None else None, os=otypes.OperatingSystem( type=self.param('operating_system'), ) if self.param('operating_system') else None, memory=convert_to_bytes( self.param('memory') ) if self.param('memory') else None, soundcard_enabled=self.param('soundcard_enabled'), usb=( otypes.Usb(enabled=self.param('usb_support')) ) if self.param('usb_support') is not None else None, sso=( otypes.Sso( methods=[otypes.Method(id=otypes.SsoMethod.GUEST_AGENT)] if self.param('sso') else [] ) ) if self.param('sso') is not None else None, time_zone=otypes.TimeZone( name=self.param('timezone'), ) if self.param('timezone') else None, version=otypes.TemplateVersion( base_template=self._get_base_template(), version_name=self.param('version').get('name'), ) if self.param('version') else None, memory_policy=otypes.MemoryPolicy( guaranteed=convert_to_bytes(self.param('memory_guaranteed')), ballooning=self.param('ballooning_enabled'), max=convert_to_bytes(self.param('memory_max')), ) if any(( self.param('memory_guaranteed'), self.param('ballooning_enabled'), self.param('memory_max') )) else None, io=otypes.Io( threads=self.param('io_threads'), ) if self.param('io_threads') is not None else None, initialization=self.get_initialization(), ) def _get_base_template(self): templates = self._connection.system_service().templates_service().list() for template in templates: if template.version.version_number == 1 and template.name == self.param('name'): return otypes.Template( id=template.id ) def post_update(self, entity): self.post_present(entity.id) def post_present(self, entity_id): # After creation of the VM, attach disks and NICs: entity = self._service.service(entity_id).get() self.__attach_nics(entity) def __get_vnic_profile_id(self, nic): """ Return VNIC profile ID looked up by it's name, because there can be more VNIC profiles with same name, other criteria of filter is cluster. """ vnics_service = self._connection.system_service().vnic_profiles_service() clusters_service = self._connection.system_service().clusters_service() cluster = search_by_name(clusters_service, self.param('cluster')) profiles = [ profile for profile in vnics_service.list() if profile.name == nic.get('profile_name') ] cluster_networks = [ net.id for net in self._connection.follow_link(cluster.networks) ] try: return next( profile.id for profile in profiles if profile.network.id in cluster_networks ) except StopIteration: raise Exception( "Profile '%s' was not found in cluster '%s'" % ( nic.get('profile_name'), self.param('cluster') ) ) def __attach_nics(self, entity): # Attach NICs to VM, if specified: nics_service = self._service.service(entity.id).nics_service() for nic in self.param('nics'): if search_by_name(nics_service, nic.get('name')) is None: if not self._module.check_mode: nics_service.add( otypes.Nic( name=nic.get('name'), interface=otypes.NicInterface( nic.get('interface', 'virtio') ), vnic_profile=otypes.VnicProfile( id=self.__get_vnic_profile_id(nic), ) if nic.get('profile_name') else None, mac=otypes.Mac( address=nic.get('mac_address') ) if nic.get('mac_address') else None, ) ) self.changed = True def get_initialization(self): if self._initialization is not None: return self._initialization sysprep = self.param('sysprep') cloud_init = self.param('cloud_init') cloud_init_nics = self.param('cloud_init_nics') or [] if cloud_init is not None: cloud_init_nics.append(cloud_init) if cloud_init or cloud_init_nics: self._initialization = otypes.Initialization( nic_configurations=[ otypes.NicConfiguration( boot_protocol=otypes.BootProtocol( nic.pop('nic_boot_protocol').lower() ) if nic.get('nic_boot_protocol') else None, name=nic.pop('nic_name', None), on_boot=nic.pop('nic_on_boot', None), ip=otypes.Ip( address=nic.pop('nic_ip_address', None), netmask=nic.pop('nic_netmask', None), gateway=nic.pop('nic_gateway', None), ) if ( nic.get('nic_gateway') is not None or nic.get('nic_netmask') is not None or nic.get('nic_ip_address') is not None ) else None, ) for nic in cloud_init_nics if ( nic.get('nic_gateway') is not None or nic.get('nic_netmask') is not None or nic.get('nic_ip_address') is not None or nic.get('nic_boot_protocol') is not None or nic.get('nic_on_boot') is not None ) ] if cloud_init_nics else None, **cloud_init ) elif sysprep: self._initialization = otypes.Initialization( **sysprep ) return self._initialization def update_check(self, entity): template_display = entity.display return ( equal(self._module.params.get('cluster'), get_link_name(self._connection, entity.cluster)) and equal(self._module.params.get('description'), entity.description) and equal(self.param('operating_system'), str(entity.os.type)) and equal(self.param('name'), str(entity.name)) and equal(self.param('smartcard_enabled'), getattr(template_display, 'smartcard_enabled', False)) and equal(self.param('soundcard_enabled'), entity.soundcard_enabled) and equal(self.param('ballooning_enabled'), entity.memory_policy.ballooning) and equal(self.param('sso'), True if entity.sso.methods else False) and equal(self.param('timezone'), getattr(entity.time_zone, 'name', None)) and equal(self.param('usb_support'), entity.usb.enabled) and equal(convert_to_bytes(self.param('memory_guaranteed')), entity.memory_policy.guaranteed) and equal(convert_to_bytes(self.param('memory_max')), entity.memory_policy.max) and equal(convert_to_bytes(self.param('memory')), entity.memory) and equal(self._module.params.get('cpu_profile'), get_link_name(self._connection, entity.cpu_profile)) and equal(self.param('io_threads'), entity.io.threads) ) def _get_export_domain_service(self): provider_name = self._module.params['export_domain'] or self._module.params['image_provider'] export_sds_service = self._connection.system_service().storage_domains_service() export_sd = search_by_name(export_sds_service, provider_name) if export_sd is None: raise ValueError( "Export storage domain/Image Provider '%s' wasn't found." % provider_name ) return export_sds_service.service(export_sd.id) def post_export_action(self, entity): self._service = self._get_export_domain_service().templates_service() def post_import_action(self, entity): self._service = self._connection.system_service().templates_service() def _get_role_mappings(module): roleMappings = list() for roleMapping in module.params['role_mappings']: roleMappings.append( otypes.RegistrationRoleMapping( from_=otypes.Role( name=roleMapping['source_name'], ) if roleMapping['source_name'] else None, to=otypes.Role( name=roleMapping['dest_name'], ) if roleMapping['dest_name'] else None, ) ) return roleMappings def _get_domain_mappings(module): domainMappings = list() for domainMapping in module.params['domain_mappings']: domainMappings.append( otypes.RegistrationDomainMapping( from_=otypes.Domain( name=domainMapping['source_name'], ) if domainMapping['source_name'] else None, to=otypes.Domain( name=domainMapping['dest_name'], ) if domainMapping['dest_name'] else None, ) ) return domainMappings def _get_cluster_mappings(module): clusterMappings = list() for clusterMapping in module.params['cluster_mappings']: clusterMappings.append( otypes.RegistrationClusterMapping( from_=otypes.Cluster( name=clusterMapping['source_name'], ), to=otypes.Cluster( name=clusterMapping['dest_name'], ), ) ) return clusterMappings def _get_vnic_profile_mappings(module): vnicProfileMappings = list() for vnicProfileMapping in module.params['vnic_profile_mappings']: vnicProfileMappings.append( otypes.VnicProfileMapping( source_network_name=vnicProfileMapping['source_network_name'], source_network_profile_name=vnicProfileMapping['source_profile_name'], target_vnic_profile=otypes.VnicProfile( id=vnicProfileMapping['target_profile_id'], ) if vnicProfileMapping['target_profile_id'] else None, ) ) return vnicProfileMappings def find_subversion_template(module, templates_service): version = module.params.get('version') templates = templates_service.list() for template in templates: if version.get('number') == template.version.version_number and module.params.get('name') == template.name: return template # when user puts version number which does not exist raise ValueError( "Template with name '%s' and version '%s' in cluster '%s' was not found'" % ( module.params['name'], module.params['version']['number'], module.params['cluster'], ) ) def searchable_attributes(module): """ Return all searchable template attributes passed to module. """ attributes = { 'name': module.params.get('name'), 'cluster': module.params.get('cluster'), } return dict((k, v) for k, v in attributes.items() if v is not None) def main(): argument_spec = ovirt_full_argument_spec( state=dict( choices=['present', 'absent', 'exported', 'imported', 'registered'], default='present', ), id=dict(default=None), name=dict(default=None), vm=dict(default=None), timezone=dict(type='str'), description=dict(default=None), sso=dict(type='bool'), ballooning_enabled=dict(type='bool', default=None), cluster=dict(default=None), usb_support=dict(type='bool'), allow_partial_import=dict(default=None, type='bool'), cpu_profile=dict(default=None), clone_permissions=dict(type='bool'), export_domain=dict(default=None), storage_domain=dict(default=None), exclusive=dict(type='bool'), clone_name=dict(default=None), image_provider=dict(default=None), soundcard_enabled=dict(type='bool', default=None), smartcard_enabled=dict(type='bool', default=None), image_disk=dict(default=None, aliases=['glance_image_disk_name']), io_threads=dict(type='int', default=None), template_image_disk_name=dict(default=None), version=dict(default=None, type='dict'), seal=dict(type='bool'), vnic_profile_mappings=dict(default=[], type='list'), cluster_mappings=dict(default=[], type='list'), role_mappings=dict(default=[], type='list'), domain_mappings=dict(default=[], type='list'), operating_system=dict(type='str'), memory=dict(type='str'), memory_guaranteed=dict(type='str'), memory_max=dict(type='str'), nics=dict(type='list', default=[]), cloud_init=dict(type='dict'), cloud_init_nics=dict(type='list', default=[]), sysprep=dict(type='dict'), ) module = AnsibleModule( argument_spec=argument_spec, supports_check_mode=True, required_one_of=[['id', 'name']], ) check_sdk(module) try: auth = module.params.pop('auth') connection = create_connection(auth) templates_service = connection.system_service().templates_service() templates_module = TemplatesModule( connection=connection, module=module, service=templates_service, ) entity = None if module.params['version'] is not None and module.params['version'].get('number') is not None: entity = find_subversion_template(module, templates_service) state = module.params['state'] if state == 'present': force_create = False if entity is None and module.params['version'] is not None: force_create = True ret = templates_module.create( entity=entity, # When user want to create new template subversion, we must make sure # template is force created as it already exists, but new version should be created. force_create=force_create, result_state=otypes.TemplateStatus.OK, search_params=searchable_attributes(module), clone_permissions=module.params['clone_permissions'], seal=module.params['seal'], ) elif state == 'absent': ret = templates_module.remove(entity=entity) elif state == 'exported': template = templates_module.search_entity() if entity is not None: template = entity export_service = templates_module._get_export_domain_service() export_template = search_by_attributes(export_service.templates_service(), id=template.id) ret = templates_module.action( entity=template, action='export', action_condition=lambda t: export_template is None or module.params['exclusive'], wait_condition=lambda t: t is not None, post_action=templates_module.post_export_action, storage_domain=otypes.StorageDomain(id=export_service.get().id), exclusive=module.params['exclusive'], ) elif state == 'imported': template = templates_module.search_entity() if entity is not None: template = entity if template and module.params['clone_name'] is None: ret = templates_module.create( result_state=otypes.TemplateStatus.OK, ) else: kwargs = {} if module.params['image_provider']: kwargs.update( disk=otypes.Disk( name=module.params['template_image_disk_name'] or module.params['image_disk'] ), template=otypes.Template( name=module.params['name'] if module.params['clone_name'] is None else module.params['clone_name'], ), clone=True if module.params['clone_name'] is not None else False, import_as_template=True, ) if module.params['image_disk']: # We need to refresh storage domain to get list of images: templates_module._get_export_domain_service().images_service().list() glance_service = connection.system_service().openstack_image_providers_service() image_provider = search_by_name(glance_service, module.params['image_provider']) images_service = glance_service.service(image_provider.id).images_service() else: images_service = templates_module._get_export_domain_service().templates_service() template_name = module.params['image_disk'] or module.params['name'] entity = search_by_name(images_service, template_name) if entity is None: raise Exception("Image/template '%s' was not found." % template_name) images_service.service(entity.id).import_( storage_domain=otypes.StorageDomain( name=module.params['storage_domain'] ) if module.params['storage_domain'] else None, cluster=otypes.Cluster( name=module.params['cluster'] ) if module.params['cluster'] else None, **kwargs ) # Wait for template to appear in system: template = templates_module.wait_for_import( condition=lambda t: t.status == otypes.TemplateStatus.OK ) ret = templates_module.create(result_state=otypes.TemplateStatus.OK) ret = { 'changed': True, 'id': template.id, 'template': get_dict_of_struct(template), } elif state == 'registered': storage_domains_service = connection.system_service().storage_domains_service() # Find the storage domain with unregistered template: sd_id = get_id_by_name(storage_domains_service, module.params['storage_domain']) storage_domain_service = storage_domains_service.storage_domain_service(sd_id) templates_service = storage_domain_service.templates_service() # Find the unregistered Template we want to register: templates = templates_service.list(unregistered=True) template = next( (t for t in templates if (t.id == module.params['id'] or t.name == module.params['name'])), None ) changed = False if template is None: template = templates_module.search_entity() if template is None: raise ValueError( "Template '%s(%s)' wasn't found." % (module.params['name'], module.params['id']) ) else: # Register the template into the system: changed = True template_service = templates_service.template_service(template.id) template_service.register( allow_partial_import=module.params['allow_partial_import'], cluster=otypes.Cluster( name=module.params['cluster'] ) if module.params['cluster'] else None, vnic_profile_mappings=_get_vnic_profile_mappings(module) if module.params['vnic_profile_mappings'] else None, registration_configuration=otypes.RegistrationConfiguration( cluster_mappings=_get_cluster_mappings(module), role_mappings=_get_role_mappings(module), domain_mappings=_get_domain_mappings(module), ) if (module.params['cluster_mappings'] or module.params['role_mappings'] or module.params['domain_mappings']) else None ) if module.params['wait']: template = templates_module.wait_for_import() else: # Fetch template to initialize return. template = template_service.get() ret = templates_module.create(result_state=otypes.TemplateStatus.OK) ret = { 'changed': changed, 'id': template.id, 'template': get_dict_of_struct(template) } module.exit_json(**ret) except Exception as e: module.fail_json(msg=str(e), exception=traceback.format_exc()) finally: connection.close(logout=auth.get('token') is None) if __name__ == "__main__": main()
2014c2g1/c2g1
refs/heads/master
w2/static/Brython2.0.0-20140209-164925/Lib/antigravity.py
917
import webbrowser import hashlib webbrowser.open("http://xkcd.com/353/") def geohash(latitude, longitude, datedow): '''Compute geohash() using the Munroe algorithm. >>> geohash(37.421542, -122.085589, b'2005-05-26-10458.68') 37.857713 -122.544543 ''' # http://xkcd.com/426/ h = hashlib.md5(datedow).hexdigest() p, q = [('%f' % float.fromhex('0.' + x)) for x in (h[:16], h[16:32])] print('%d%s %d%s' % (latitude, p[1:], longitude, q[1:]))
pyrocko/pyrocko
refs/heads/master
test/base/test_obspy_compat.py
1
from __future__ import division, print_function, absolute_import import unittest from .. import common import pyrocko.trace from pyrocko import util, io, model, pile if common.have_obspy(): import obspy from pyrocko import obspy_compat obspy_compat.plant() def close_win(win): win.close() @common.require_obspy class ObsPyCompatTestCase(unittest.TestCase): @common.require_gui def test_obspy_snuffle(self): fn = common.test_data_file('test1.mseed') stream = obspy.read(fn) stream.snuffle(launch_hook=close_win, instant_close=True) trace = stream[0] trace.snuffle(launch_hook=close_win, instant_close=True) @common.require_gui def test_obspy_fiddle(self): fn = common.test_data_file('test1.mseed') stream = obspy.read(fn) stream2 = stream.fiddle(launch_hook=close_win, instant_close=True) # noqa trace = stream[0] trace2 = trace.fiddle(launch_hook=close_win, instant_close=True) # noqa def test_to_obspy_trace(self): traces = io.load(common.test_data_file('test1.mseed')) for tr in traces: obs_tr = tr.to_obspy_trace() assert isinstance(obs_tr, obspy.Trace) assert obs_tr.data.size == tr.data_len() obs_stats = obs_tr.stats for attr in ('network', 'station', 'location', 'channel'): assert obs_stats.__getattr__(attr) == tr.__getattribute__(attr) def test_to_obspy_stream(self): pl = pile.Pile() pl.load_files([common.test_data_file('test1.mseed')], show_progress=False) st = pl.to_obspy_stream() assert isinstance(st, obspy.Stream) assert len(st) == len([tr for tr in pl.iter_all()]) for tr in st: assert isinstance(tr, obspy.Trace) def test_to_pyrocko_traces(self): st = obspy.read(common.test_data_file('test1.mseed')) traces = st.to_pyrocko_traces() assert isinstance(traces, list) for tr in traces: assert isinstance(tr, pyrocko.trace.Trace) for tr in st: assert isinstance(tr.to_pyrocko_trace(), pyrocko.trace.Trace) def test_to_pyrocko_stations(self): fn = common.test_data_file('geeil.geofon.xml') inventory = obspy.read_inventory(fn) for sta in inventory.to_pyrocko_stations(): assert isinstance(sta, model.Station) def test_to_pyrocko_events(self): from obspy.clients.fdsn.client import Client client = Client('IRIS') cat = client.get_events(eventid=609301) events = cat.to_pyrocko_events() self.assertEqual(len(events), len(cat)) if __name__ == "__main__": util.setup_logging('test_obspy_compat', 'warning') unittest.main()
sysadmin75/ansible
refs/heads/devel
test/units/module_utils/urls/test_RedirectHandlerFactory.py
70
# -*- coding: utf-8 -*- # (c) 2018 Matt Martz <matt@sivel.net> # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) from __future__ import absolute_import, division, print_function __metaclass__ = type from ansible.module_utils.urls import HAS_SSLCONTEXT, RedirectHandlerFactory, urllib_request, urllib_error from ansible.module_utils.six import StringIO import pytest @pytest.fixture def urllib_req(): req = urllib_request.Request( 'https://ansible.com/' ) return req @pytest.fixture def request_body(): return StringIO('TESTS') def test_no_redirs(urllib_req, request_body): handler = RedirectHandlerFactory('none', False) inst = handler() with pytest.raises(urllib_error.HTTPError): inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') def test_urllib2_redir(urllib_req, request_body, mocker): redir_request_mock = mocker.patch('ansible.module_utils.urls.urllib_request.HTTPRedirectHandler.redirect_request') handler = RedirectHandlerFactory('urllib2', False) inst = handler() inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') redir_request_mock.assert_called_once_with(inst, urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') def test_all_redir(urllib_req, request_body, mocker): req_mock = mocker.patch('ansible.module_utils.urls.RequestWithMethod') handler = RedirectHandlerFactory('all', False) inst = handler() inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') req_mock.assert_called_once_with('https://docs.ansible.com/', data=None, headers={}, method='GET', origin_req_host='ansible.com', unverifiable=True) def test_all_redir_post(request_body, mocker): handler = RedirectHandlerFactory('all', False) inst = handler() req = urllib_request.Request( 'https://ansible.com/', 'POST' ) req_mock = mocker.patch('ansible.module_utils.urls.RequestWithMethod') inst.redirect_request(req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') req_mock.assert_called_once_with('https://docs.ansible.com/', data=None, headers={}, method='GET', origin_req_host='ansible.com', unverifiable=True) def test_redir_headers_removal(urllib_req, request_body, mocker): req_mock = mocker.patch('ansible.module_utils.urls.RequestWithMethod') handler = RedirectHandlerFactory('all', False) inst = handler() urllib_req.headers = { 'Content-Type': 'application/json', 'Content-Length': 100, 'Foo': 'bar', } inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') req_mock.assert_called_once_with('https://docs.ansible.com/', data=None, headers={'Foo': 'bar'}, method='GET', origin_req_host='ansible.com', unverifiable=True) def test_redir_url_spaces(urllib_req, request_body, mocker): req_mock = mocker.patch('ansible.module_utils.urls.RequestWithMethod') handler = RedirectHandlerFactory('all', False) inst = handler() inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/foo bar') req_mock.assert_called_once_with('https://docs.ansible.com/foo%20bar', data=None, headers={}, method='GET', origin_req_host='ansible.com', unverifiable=True) def test_redir_safe(urllib_req, request_body, mocker): req_mock = mocker.patch('ansible.module_utils.urls.RequestWithMethod') handler = RedirectHandlerFactory('safe', False) inst = handler() inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') req_mock.assert_called_once_with('https://docs.ansible.com/', data=None, headers={}, method='GET', origin_req_host='ansible.com', unverifiable=True) def test_redir_safe_not_safe(request_body): handler = RedirectHandlerFactory('safe', False) inst = handler() req = urllib_request.Request( 'https://ansible.com/', 'POST' ) with pytest.raises(urllib_error.HTTPError): inst.redirect_request(req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') def test_redir_no_error_on_invalid(urllib_req, request_body): handler = RedirectHandlerFactory('invalid', False) inst = handler() with pytest.raises(urllib_error.HTTPError): inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') def test_redir_validate_certs(urllib_req, request_body, mocker): opener_mock = mocker.patch('ansible.module_utils.urls.urllib_request._opener') handler = RedirectHandlerFactory('all', True) inst = handler() inst.redirect_request(urllib_req, request_body, 301, '301 Moved Permanently', {}, 'https://docs.ansible.com/') assert opener_mock.add_handler.call_count == int(not HAS_SSLCONTEXT) def test_redir_http_error_308_urllib2(urllib_req, request_body): handler = RedirectHandlerFactory('urllib2', False) inst = handler() with pytest.raises(urllib_error.HTTPError): inst.redirect_request(urllib_req, request_body, 308, '308 Permanent Redirect', {}, 'https://docs.ansible.com/')
souravbadami/oppia
refs/heads/develop
core/controllers/features_test.py
1
# Copyright 2019 The Oppia Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS-IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for fetching the features Oppia provides to its users.""" from core.domain import config_domain from core.domain import rights_manager from core.domain import user_services from core.tests import test_utils import feconf def exploration_features_url(exp_id): """Returns URL for getting which features the given exploration supports.""" return '%s/%s' % (feconf.EXPLORATION_FEATURES_PREFIX, exp_id) class ExplorationFeaturesTestBase(test_utils.GenericTestBase): """Does common exploration set up for testing feature handlers.""" EXP_ID = 'expId' def setUp(self): super(ExplorationFeaturesTestBase, self).setUp() self.signup(self.EDITOR_EMAIL, self.EDITOR_USERNAME) editor_id = self.get_user_id_from_email(self.EDITOR_EMAIL) self.save_new_valid_exploration( self.EXP_ID, editor_id, title='Explore!', end_state_name='END') editor_actions_info = user_services.UserActionsInfo(editor_id) rights_manager.publish_exploration(editor_actions_info, self.EXP_ID) class ExplorationPlaythroughRecordingFeatureTest(ExplorationFeaturesTestBase): """Tests for fetching whether playthrough recording is enabled.""" def test_can_record_playthroughs_in_whitelisted_explorations(self): self.set_config_property( config_domain.WHITELISTED_EXPLORATION_IDS_FOR_PLAYTHROUGHS, new_config_value=[self.EXP_ID]) json_response = self.get_json(exploration_features_url(self.EXP_ID)) self.assertTrue(json_response['is_exploration_whitelisted']) def test_can_not_record_playthroughs_with_empty_whitelist(self): self.set_config_property( config_domain.WHITELISTED_EXPLORATION_IDS_FOR_PLAYTHROUGHS, new_config_value=[]) json_response = self.get_json(exploration_features_url(self.EXP_ID)) self.assertFalse(json_response['is_exploration_whitelisted']) def test_can_not_record_playthroughs_for_exploration_not_in_whitelist(self): self.set_config_property( config_domain.WHITELISTED_EXPLORATION_IDS_FOR_PLAYTHROUGHS, new_config_value=[self.EXP_ID + '-differentiate']) json_response = self.get_json(exploration_features_url(self.EXP_ID)) self.assertFalse(json_response['is_exploration_whitelisted']) class ExplorationImprovementsTabFeatureTest(ExplorationFeaturesTestBase): """Tests for fetching whether the improvements tab is enabled.""" def test_improvements_tab_is_enabled(self): self.set_config_property( config_domain.IS_IMPROVEMENTS_TAB_ENABLED, new_config_value=True) json_response = self.get_json(exploration_features_url(self.EXP_ID)) self.assertTrue(json_response['is_improvements_tab_enabled']) def test_improvements_tab_is_disabled(self): self.set_config_property( config_domain.IS_IMPROVEMENTS_TAB_ENABLED, new_config_value=False) json_response = self.get_json(exploration_features_url(self.EXP_ID)) self.assertFalse(json_response['is_improvements_tab_enabled'])
MrSurly/micropython
refs/heads/master
tests/basics/builtin_round.py
103
# test round() with integral values tests = [ False, True, 0, 1, -1, 10 ] for t in tests: print(round(t))
Tejal011089/trufil-erpnext
refs/heads/master
erpnext/setup/doctype/sales_person/test_sales_person.py
104
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors # License: GNU General Public License v3. See license.txt from __future__ import unicode_literals test_dependencies = ["Employee"] import frappe test_records = frappe.get_test_records('Sales Person')
flh/odoo
refs/heads/master
addons/product_email_template/__openerp__.py
65
# -*- coding: utf-8 -*- { 'name': 'Product Email Template', 'depends': ['account'], 'author': 'OpenERP SA', 'category': 'Accounting & Finance', 'description': """ Add email templates to products to be send on invoice confirmation ================================================================== With this module, link your products to a template to send complete information and tools to your customer. For instance when invoicing a training, the training agenda and materials will automatically be sent to your customers.' """, 'website': 'http://www.openerp.com', 'demo': [ 'data/product_demo.xml', ], 'data': [ 'views/product_view.xml', 'views/email_template_view.xml', ], 'installable': True, 'auto_install': False, }
MalloyPower/parsing-python
refs/heads/master
front-end/testsuite-python-lib/Python-2.1/Lib/py_compile.py
2
"""Routine to "compile" a .py file to a .pyc (or .pyo) file. This module has intimate knowledge of the format of .pyc files. """ import imp MAGIC = imp.get_magic() __all__ = ["compile"] def wr_long(f, x): """Internal; write a 32-bit int to a file in little-endian order.""" f.write(chr( x & 0xff)) f.write(chr((x >> 8) & 0xff)) f.write(chr((x >> 16) & 0xff)) f.write(chr((x >> 24) & 0xff)) def compile(file, cfile=None, dfile=None): """Byte-compile one Python source file to Python bytecode. Arguments: file: source filename cfile: target filename; defaults to source with 'c' or 'o' appended ('c' normally, 'o' in optimizing mode, giving .pyc or .pyo) dfile: purported filename; defaults to source (this is the filename that will show up in error messages) Note that it isn't necessary to byte-compile Python modules for execution efficiency -- Python itself byte-compiles a module when it is loaded, and if it can, writes out the bytecode to the corresponding .pyc (or .pyo) file. However, if a Python installation is shared between users, it is a good idea to byte-compile all modules upon installation, since other users may not be able to write in the source directories, and thus they won't be able to write the .pyc/.pyo file, and then they would be byte-compiling every module each time it is loaded. This can slow down program start-up considerably. See compileall.py for a script/module that uses this module to byte-compile all installed files (or all files in selected directories). """ import os, marshal, __builtin__ f = open(file) try: timestamp = long(os.fstat(f.fileno())[8]) except AttributeError: timestamp = long(os.stat(file)[8]) codestring = f.read() # If parsing from a string, line breaks are \n (see parsetok.c:tok_nextc) # Replace will return original string if pattern is not found, so # we don't need to check whether it is found first. codestring = codestring.replace("\r\n","\n") codestring = codestring.replace("\r","\n") f.close() if codestring and codestring[-1] != '\n': codestring = codestring + '\n' try: codeobject = __builtin__.compile(codestring, dfile or file, 'exec') except SyntaxError, detail: import traceback, sys lines = traceback.format_exception_only(SyntaxError, detail) for line in lines: sys.stderr.write(line.replace('File "<string>"', 'File "%s"' % (dfile or file))) return if not cfile: cfile = file + (__debug__ and 'c' or 'o') fc = open(cfile, 'wb') fc.write('\0\0\0\0') wr_long(fc, timestamp) marshal.dump(codeobject, fc) fc.flush() fc.seek(0, 0) fc.write(MAGIC) fc.close() if os.name == 'mac': import macfs macfs.FSSpec(cfile).SetCreatorType('Pyth', 'PYC ')
poljeff/odoo
refs/heads/8.0
addons/l10n_fr/report/compute_resultant_report.py
374
# -*- coding: utf-8 -*- # # # Copyright (c) 2008 JAILLET Simon - CrysaLEAD - www.crysalead.fr # # WARNING: This program as such is intended to be used by professional # programmers who take the whole responsability of assessing all potential # consequences resulting from its eventual inadequacies and bugs # End users who are looking for a ready-to-use solution with commercial # garantees and support are strongly adviced to contract a Free Software # Service Company # # This program is Free Software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA # # import base_report from openerp.osv import osv class cdr(base_report.base_report): def __init__(self, cr, uid, name, context): super(cdr, self).__init__(cr, uid, name, context) def set_context(self, objects, data, ids): super(cdr, self).set_context(objects, data, ids) self._load('cdr', self.localcontext['data']['form']) self._set_variable( 'ct1', self.localcontext['cdrc1']+self.localcontext['cdrc2']+self.localcontext['cdrc3']+ self.localcontext['cdrc4']+self.localcontext['cdrc5']+self.localcontext['cdrc6']+ self.localcontext['cdrc7']+self.localcontext['cdrc8']+self.localcontext['cdrc9']+ self.localcontext['cdrc10']+self.localcontext['cdrc11']+self.localcontext['cdrc12']+ self.localcontext['cdrc13']+self.localcontext['cdrc14']+self.localcontext['cdrc15'] ) self._set_variable( 'ct3', self.localcontext['cdrc17']+self.localcontext['cdrc18']+self.localcontext['cdrc19']+ self.localcontext['cdrc20'] ) self._set_variable( 'ct4', self.localcontext['cdrc21']+self.localcontext['cdrc22']+self.localcontext['cdrc23'] ) self._set_variable( 'charges', self.localcontext['ct1']+self.localcontext['cdrc16']+self.localcontext['ct3']+ self.localcontext['ct4']+self.localcontext['cdrc24']+self.localcontext['cdrc25'] ) self._set_variable( 'pta', self.localcontext['cdrp1']+self.localcontext['cdrp2'] ) self._set_variable( 'ptb', self.localcontext['cdrp3']+self.localcontext['cdrp4']+self.localcontext['cdrp5']+ self.localcontext['cdrp6']+self.localcontext['cdrp7'] ) self._set_variable( 'pt1', self.localcontext['pta']+self.localcontext['ptb'] ) self._set_variable( 'pt3', self.localcontext['cdrp9']+self.localcontext['cdrp10']+self.localcontext['cdrp11']+ self.localcontext['cdrp12']+self.localcontext['cdrp13']+self.localcontext['cdrp14'] ) self._set_variable( 'pt4', self.localcontext['cdrp15']+self.localcontext['cdrp16']+self.localcontext['cdrp17'] ) self._set_variable( 'produits', self.localcontext['pt1']+self.localcontext['cdrp8']+self.localcontext['pt3']+ self.localcontext['pt4'] ) class wrapped_report_resultat(osv.AbstractModel): _name = 'report.l10n_fr.report_l10nfrresultat' _inherit = 'report.abstract_report' _template = 'l10n_fr.report_l10nfrresultat' _wrapped_report_class = cdr # vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:
gdub/django
refs/heads/master
django/utils/inspect.py
146
from __future__ import absolute_import import inspect from django.utils import six def getargspec(func): if six.PY2: return inspect.getargspec(func) sig = inspect.signature(func) args = [ p.name for p in sig.parameters.values() if p.kind == inspect.Parameter.POSITIONAL_OR_KEYWORD ] varargs = [ p.name for p in sig.parameters.values() if p.kind == inspect.Parameter.VAR_POSITIONAL ] varargs = varargs[0] if varargs else None varkw = [ p.name for p in sig.parameters.values() if p.kind == inspect.Parameter.VAR_KEYWORD ] varkw = varkw[0] if varkw else None defaults = [ p.default for p in sig.parameters.values() if p.kind == inspect.Parameter.POSITIONAL_OR_KEYWORD and p.default is not p.empty ] or None return args, varargs, varkw, defaults def get_func_args(func): if six.PY2: argspec = inspect.getargspec(func) return argspec.args[1:] # ignore 'self' sig = inspect.signature(func) return [ arg_name for arg_name, param in sig.parameters.items() if param.kind == inspect.Parameter.POSITIONAL_OR_KEYWORD ] def func_accepts_kwargs(func): if six.PY2: # Not all callables are inspectable with getargspec, so we'll # try a couple different ways but in the end fall back on assuming # it is -- we don't want to prevent registration of valid but weird # callables. try: argspec = inspect.getargspec(func) except TypeError: try: argspec = inspect.getargspec(func.__call__) except (TypeError, AttributeError): argspec = None return not argspec or argspec[2] is not None return any( p for p in inspect.signature(func).parameters.values() if p.kind == p.VAR_KEYWORD ) def func_has_no_args(func): args = inspect.getargspec(func)[0] if six.PY2 else [ p for p in inspect.signature(func).parameters.values() if p.kind == p.POSITIONAL_OR_KEYWORD and p.default is p.empty ] return len(args) == 1 def func_supports_parameter(func, parameter): if six.PY3: return parameter in inspect.signature(func).parameters else: args, varargs, varkw, defaults = inspect.getargspec(func) return parameter in args
gunicorn/gunicorn
refs/heads/master
examples/frameworks/django/testing/testing/apps/someapp/views.py
7
# Create your views here. import csv import io import os from django import forms from django.http import HttpResponse from django.shortcuts import render_to_response from django.template import RequestContext import tempfile class MsgForm(forms.Form): subject = forms.CharField(max_length=100) message = forms.CharField() f = forms.FileField() def home(request): from django.conf import settings print(settings.SOME_VALUE) subject = None message = None size = 0 print(request.META) if request.POST: form = MsgForm(request.POST, request.FILES) print(request.FILES) if form.is_valid(): subject = form.cleaned_data['subject'] message = form.cleaned_data['message'] f = request.FILES['f'] if not hasattr(f, "fileno"): size = len(f.read()) else: try: size = int(os.fstat(f.fileno())[6]) except io.UnsupportedOperation: size = len(f.read()) else: form = MsgForm() return render_to_response('home.html', { 'form': form, 'subject': subject, 'message': message, 'size': size }, RequestContext(request)) def acsv(request): rows = [ {'a': 1, 'b': 2}, {'a': 3, 'b': 3} ] response = HttpResponse(mimetype='text/csv') response['Content-Disposition'] = 'attachment; filename=report.csv' writer = csv.writer(response) writer.writerow(['a', 'b']) for r in rows: writer.writerow([r['a'], r['b']]) return response
Lekanich/intellij-community
refs/heads/master
python/testData/keywordCompletion/continue.py
83
for x in []: conti<caret>
toshywoshy/ansible
refs/heads/devel
lib/ansible/modules/cloud/google/gcp_bigquery_table.py
6
#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright (C) 2017 Google # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) # ---------------------------------------------------------------------------- # # *** AUTO GENERATED CODE *** AUTO GENERATED CODE *** # # ---------------------------------------------------------------------------- # # This file is automatically generated by Magic Modules and manual # changes will be clobbered when the file is regenerated. # # Please read more about how to change this file at # https://www.github.com/GoogleCloudPlatform/magic-modules # # ---------------------------------------------------------------------------- from __future__ import absolute_import, division, print_function __metaclass__ = type ################################################################################ # Documentation ################################################################################ ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ["preview"], 'supported_by': 'community'} DOCUMENTATION = ''' --- module: gcp_bigquery_table description: - A Table that belongs to a Dataset . short_description: Creates a GCP Table version_added: '2.8' author: Google Inc. (@googlecloudplatform) requirements: - python >= 2.6 - requests >= 2.18.4 - google-auth >= 1.3.0 options: state: description: - Whether the given object should exist in GCP choices: - present - absent default: present type: str table_reference: description: - Reference describing the ID of this table. required: false type: dict suboptions: dataset_id: description: - The ID of the dataset containing this table. required: false type: str project_id: description: - The ID of the project containing this table. required: false type: str table_id: description: - The ID of the table. required: false type: str clustering: description: - One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. required: false type: list version_added: '2.9' description: description: - A user-friendly description of the dataset. required: false type: str friendly_name: description: - A descriptive name for this table. required: false type: str labels: description: - The labels associated with this dataset. You can use these to organize and group your datasets . required: false type: dict name: description: - Name of the table. required: false type: str num_rows: description: - The number of rows of data in this table, excluding any data in the streaming buffer. required: false type: int version_added: '2.9' view: description: - The view definition. required: false type: dict suboptions: use_legacy_sql: description: - Specifies whether to use BigQuery's legacy SQL for this view . required: false type: bool user_defined_function_resources: description: - Describes user-defined function resources used in the query. required: false type: list suboptions: inline_code: description: - An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. required: false type: str resource_uri: description: - A code resource to load from a Google Cloud Storage URI (gs://bucket/path). required: false type: str time_partitioning: description: - If specified, configures time-based partitioning for this table. required: false type: dict suboptions: expiration_ms: description: - Number of milliseconds for which to keep the storage for a partition. required: false type: int field: description: - If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. required: false type: str version_added: '2.9' type: description: - The only type supported is DAY, which will generate one partition per day. - 'Some valid choices include: "DAY"' required: false type: str schema: description: - Describes the schema of this table. required: false type: dict suboptions: fields: description: - Describes the fields in a table. required: false type: list suboptions: description: description: - The field description. The maximum length is 1,024 characters. required: false type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD. required: false type: list mode: description: - The field mode. - 'Some valid choices include: "NULLABLE", "REQUIRED", "REPEATED"' required: false type: str name: description: - The field name. required: false type: str type: description: - The field data type. - 'Some valid choices include: "STRING", "BYTES", "INTEGER", "FLOAT", "TIMESTAMP", "DATE", "TIME", "DATETIME", "RECORD"' required: false type: str encryption_configuration: description: - Custom encryption configuration. required: false type: dict suboptions: kms_key_name: description: - Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. required: false type: str expiration_time: description: - The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. required: false type: int external_data_configuration: description: - Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. required: false type: dict suboptions: autodetect: description: - Try to detect schema and format options automatically. Any option specified explicitly will be honored. required: false type: bool compression: description: - The compression type of the data source. - 'Some valid choices include: "GZIP", "NONE"' required: false type: str ignore_unknown_values: description: - Indicates if BigQuery should allow extra values that are not represented in the table schema . required: false type: bool max_bad_records: description: - The maximum number of bad records that BigQuery can ignore when reading data . required: false default: '0' type: int source_format: description: - The data format. - 'Some valid choices include: "CSV", "GOOGLE_SHEETS", "NEWLINE_DELIMITED_JSON", "AVRO", "DATASTORE_BACKUP", "BIGTABLE"' required: false type: str source_uris: description: - The fully-qualified URIs that point to your data in Google Cloud. - 'For Google Cloud Storage URIs: Each URI can contain one ''*'' wildcard character and it must come after the ''bucket'' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the ''*'' wildcard character is not allowed.' required: false type: list schema: description: - The schema for the data. Schema is required for CSV and JSON formats. required: false type: dict suboptions: fields: description: - Describes the fields in a table. required: false type: list suboptions: description: description: - The field description. required: false type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD . required: false type: list mode: description: - Field mode. - 'Some valid choices include: "NULLABLE", "REQUIRED", "REPEATED"' required: false type: str name: description: - Field name. required: false type: str type: description: - Field data type. - 'Some valid choices include: "STRING", "BYTES", "INTEGER", "FLOAT", "TIMESTAMP", "DATE", "TIME", "DATETIME", "RECORD"' required: false type: str google_sheets_options: description: - Additional options if sourceFormat is set to GOOGLE_SHEETS. required: false type: dict suboptions: skip_leading_rows: description: - The number of rows at the top of a Google Sheet that BigQuery will skip when reading the data. required: false default: '0' type: int csv_options: description: - Additional properties to set if sourceFormat is set to CSV. required: false type: dict suboptions: allow_jagged_rows: description: - Indicates if BigQuery should accept rows that are missing trailing optional columns . required: false type: bool allow_quoted_newlines: description: - Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file . required: false type: bool encoding: description: - The character encoding of the data. - 'Some valid choices include: "UTF-8", "ISO-8859-1"' required: false type: str field_delimiter: description: - The separator for fields in a CSV file. required: false type: str quote: description: - The value that is used to quote data sections in a CSV file. required: false type: str skip_leading_rows: description: - The number of rows at the top of a CSV file that BigQuery will skip when reading the data. required: false default: '0' type: int bigtable_options: description: - Additional options if sourceFormat is set to BIGTABLE. required: false type: dict suboptions: ignore_unspecified_column_families: description: - If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema . required: false type: bool read_rowkey_as_string: description: - If field is true, then the rowkey column families will be read and converted to string. required: false type: bool column_families: description: - List of column families to expose in the table schema along with their types. required: false type: list suboptions: columns: description: - Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. required: false type: list suboptions: encoding: description: - The encoding of the values when the type is not STRING. - 'Some valid choices include: "TEXT", "BINARY"' required: false type: str field_name: description: - If the qualifier is not a valid BigQuery field identifier, a valid identifier must be provided as the column field name and is used as field name in queries. required: false type: str only_read_latest: description: - If this is set, only the latest version of value in this column are exposed . required: false type: bool qualifier_string: description: - Qualifier of the column. required: true type: str type: description: - The type to convert the value in cells of this column. - 'Some valid choices include: "BYTES", "STRING", "INTEGER", "FLOAT", "BOOLEAN"' required: false type: str encoding: description: - The encoding of the values when the type is not STRING. - 'Some valid choices include: "TEXT", "BINARY"' required: false type: str family_id: description: - Identifier of the column family. required: false type: str only_read_latest: description: - If this is set only the latest version of value are exposed for all columns in this column family . required: false type: bool type: description: - The type to convert the value in cells of this column family. - 'Some valid choices include: "BYTES", "STRING", "INTEGER", "FLOAT", "BOOLEAN"' required: false type: str dataset: description: - Name of the dataset. required: false type: str project: description: - The Google Cloud Platform project to use. type: str auth_kind: description: - The type of credential used. type: str required: true choices: - application - machineaccount - serviceaccount service_account_contents: description: - The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it. type: jsonarg service_account_file: description: - The path of a Service Account JSON file if serviceaccount is selected as type. type: path service_account_email: description: - An optional service account email address if machineaccount is selected and the user does not wish to use the default email. type: str scopes: description: - Array of scopes to be used type: list env_type: description: - Specifies which Ansible environment you're running this module within. - This should not be set unless you know what you're doing. - This only alters the User Agent string for any API requests. type: str ''' EXAMPLES = ''' - name: create a dataset gcp_bigquery_dataset: name: example_dataset dataset_reference: dataset_id: example_dataset project: "{{ gcp_project }}" auth_kind: "{{ gcp_cred_kind }}" service_account_file: "{{ gcp_cred_file }}" state: present register: dataset - name: create a table gcp_bigquery_table: name: example_table dataset: example_dataset table_reference: dataset_id: example_dataset project_id: test_project table_id: example_table project: test_project auth_kind: serviceaccount service_account_file: "/tmp/auth.pem" state: present ''' RETURN = ''' tableReference: description: - Reference describing the ID of this table. returned: success type: complex contains: datasetId: description: - The ID of the dataset containing this table. returned: success type: str projectId: description: - The ID of the project containing this table. returned: success type: str tableId: description: - The ID of the table. returned: success type: str clustering: description: - One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. returned: success type: list creationTime: description: - The time when this dataset was created, in milliseconds since the epoch. returned: success type: int description: description: - A user-friendly description of the dataset. returned: success type: str friendlyName: description: - A descriptive name for this table. returned: success type: str id: description: - An opaque ID uniquely identifying the table. returned: success type: str labels: description: - The labels associated with this dataset. You can use these to organize and group your datasets . returned: success type: dict lastModifiedTime: description: - The time when this table was last modified, in milliseconds since the epoch. returned: success type: int location: description: - The geographic location where the table resides. This value is inherited from the dataset. returned: success type: str name: description: - Name of the table. returned: success type: str numBytes: description: - The size of this table in bytes, excluding any data in the streaming buffer. returned: success type: int numLongTermBytes: description: - The number of bytes in the table that are considered "long-term storage". returned: success type: int numRows: description: - The number of rows of data in this table, excluding any data in the streaming buffer. returned: success type: int requirePartitionFilter: description: - If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. returned: success type: bool type: description: - Describes the table type. returned: success type: str view: description: - The view definition. returned: success type: complex contains: useLegacySql: description: - Specifies whether to use BigQuery's legacy SQL for this view . returned: success type: bool userDefinedFunctionResources: description: - Describes user-defined function resources used in the query. returned: success type: complex contains: inlineCode: description: - An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. returned: success type: str resourceUri: description: - A code resource to load from a Google Cloud Storage URI (gs://bucket/path). returned: success type: str timePartitioning: description: - If specified, configures time-based partitioning for this table. returned: success type: complex contains: expirationMs: description: - Number of milliseconds for which to keep the storage for a partition. returned: success type: int field: description: - If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. returned: success type: str type: description: - The only type supported is DAY, which will generate one partition per day. returned: success type: str streamingBuffer: description: - Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer. returned: success type: complex contains: estimatedBytes: description: - A lower-bound estimate of the number of bytes currently in the streaming buffer. returned: success type: int estimatedRows: description: - A lower-bound estimate of the number of rows currently in the streaming buffer. returned: success type: int oldestEntryTime: description: - Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available. returned: success type: int schema: description: - Describes the schema of this table. returned: success type: complex contains: fields: description: - Describes the fields in a table. returned: success type: complex contains: description: description: - The field description. The maximum length is 1,024 characters. returned: success type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD. returned: success type: list mode: description: - The field mode. returned: success type: str name: description: - The field name. returned: success type: str type: description: - The field data type. returned: success type: str encryptionConfiguration: description: - Custom encryption configuration. returned: success type: complex contains: kmsKeyName: description: - Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. returned: success type: str expirationTime: description: - The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. returned: success type: int externalDataConfiguration: description: - Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. returned: success type: complex contains: autodetect: description: - Try to detect schema and format options automatically. Any option specified explicitly will be honored. returned: success type: bool compression: description: - The compression type of the data source. returned: success type: str ignoreUnknownValues: description: - Indicates if BigQuery should allow extra values that are not represented in the table schema . returned: success type: bool maxBadRecords: description: - The maximum number of bad records that BigQuery can ignore when reading data . returned: success type: int sourceFormat: description: - The data format. returned: success type: str sourceUris: description: - The fully-qualified URIs that point to your data in Google Cloud. - 'For Google Cloud Storage URIs: Each URI can contain one ''*'' wildcard character and it must come after the ''bucket'' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the ''*'' wildcard character is not allowed.' returned: success type: list schema: description: - The schema for the data. Schema is required for CSV and JSON formats. returned: success type: complex contains: fields: description: - Describes the fields in a table. returned: success type: complex contains: description: description: - The field description. returned: success type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD . returned: success type: list mode: description: - Field mode. returned: success type: str name: description: - Field name. returned: success type: str type: description: - Field data type. returned: success type: str googleSheetsOptions: description: - Additional options if sourceFormat is set to GOOGLE_SHEETS. returned: success type: complex contains: skipLeadingRows: description: - The number of rows at the top of a Google Sheet that BigQuery will skip when reading the data. returned: success type: int csvOptions: description: - Additional properties to set if sourceFormat is set to CSV. returned: success type: complex contains: allowJaggedRows: description: - Indicates if BigQuery should accept rows that are missing trailing optional columns . returned: success type: bool allowQuotedNewlines: description: - Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file . returned: success type: bool encoding: description: - The character encoding of the data. returned: success type: str fieldDelimiter: description: - The separator for fields in a CSV file. returned: success type: str quote: description: - The value that is used to quote data sections in a CSV file. returned: success type: str skipLeadingRows: description: - The number of rows at the top of a CSV file that BigQuery will skip when reading the data. returned: success type: int bigtableOptions: description: - Additional options if sourceFormat is set to BIGTABLE. returned: success type: complex contains: ignoreUnspecifiedColumnFamilies: description: - If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema . returned: success type: bool readRowkeyAsString: description: - If field is true, then the rowkey column families will be read and converted to string. returned: success type: bool columnFamilies: description: - List of column families to expose in the table schema along with their types. returned: success type: complex contains: columns: description: - Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. returned: success type: complex contains: encoding: description: - The encoding of the values when the type is not STRING. returned: success type: str fieldName: description: - If the qualifier is not a valid BigQuery field identifier, a valid identifier must be provided as the column field name and is used as field name in queries. returned: success type: str onlyReadLatest: description: - If this is set, only the latest version of value in this column are exposed . returned: success type: bool qualifierString: description: - Qualifier of the column. returned: success type: str type: description: - The type to convert the value in cells of this column. returned: success type: str encoding: description: - The encoding of the values when the type is not STRING. returned: success type: str familyId: description: - Identifier of the column family. returned: success type: str onlyReadLatest: description: - If this is set only the latest version of value are exposed for all columns in this column family . returned: success type: bool type: description: - The type to convert the value in cells of this column family. returned: success type: str dataset: description: - Name of the dataset. returned: success type: str ''' ################################################################################ # Imports ################################################################################ from ansible.module_utils.gcp_utils import navigate_hash, GcpSession, GcpModule, GcpRequest, remove_nones_from_dict, replace_resource_dict import json ################################################################################ # Main ################################################################################ def main(): """Main function""" module = GcpModule( argument_spec=dict( state=dict(default='present', choices=['present', 'absent'], type='str'), table_reference=dict(type='dict', options=dict(dataset_id=dict(type='str'), project_id=dict(type='str'), table_id=dict(type='str'))), clustering=dict(type='list', elements='str'), description=dict(type='str'), friendly_name=dict(type='str'), labels=dict(type='dict'), name=dict(type='str'), num_rows=dict(type='int'), view=dict( type='dict', options=dict( use_legacy_sql=dict(type='bool'), user_defined_function_resources=dict( type='list', elements='dict', options=dict(inline_code=dict(type='str'), resource_uri=dict(type='str')) ), ), ), time_partitioning=dict(type='dict', options=dict(expiration_ms=dict(type='int'), field=dict(type='str'), type=dict(type='str'))), schema=dict( type='dict', options=dict( fields=dict( type='list', elements='dict', options=dict( description=dict(type='str'), fields=dict(type='list', elements='str'), mode=dict(type='str'), name=dict(type='str'), type=dict(type='str'), ), ) ), ), encryption_configuration=dict(type='dict', options=dict(kms_key_name=dict(type='str'))), expiration_time=dict(type='int'), external_data_configuration=dict( type='dict', options=dict( autodetect=dict(type='bool'), compression=dict(type='str'), ignore_unknown_values=dict(type='bool'), max_bad_records=dict(default=0, type='int'), source_format=dict(type='str'), source_uris=dict(type='list', elements='str'), schema=dict( type='dict', options=dict( fields=dict( type='list', elements='dict', options=dict( description=dict(type='str'), fields=dict(type='list', elements='str'), mode=dict(type='str'), name=dict(type='str'), type=dict(type='str'), ), ) ), ), google_sheets_options=dict(type='dict', options=dict(skip_leading_rows=dict(default=0, type='int'))), csv_options=dict( type='dict', options=dict( allow_jagged_rows=dict(type='bool'), allow_quoted_newlines=dict(type='bool'), encoding=dict(type='str'), field_delimiter=dict(type='str'), quote=dict(type='str'), skip_leading_rows=dict(default=0, type='int'), ), ), bigtable_options=dict( type='dict', options=dict( ignore_unspecified_column_families=dict(type='bool'), read_rowkey_as_string=dict(type='bool'), column_families=dict( type='list', elements='dict', options=dict( columns=dict( type='list', elements='dict', options=dict( encoding=dict(type='str'), field_name=dict(type='str'), only_read_latest=dict(type='bool'), qualifier_string=dict(required=True, type='str'), type=dict(type='str'), ), ), encoding=dict(type='str'), family_id=dict(type='str'), only_read_latest=dict(type='bool'), type=dict(type='str'), ), ), ), ), ), ), dataset=dict(type='str'), ) ) if not module.params['scopes']: module.params['scopes'] = ['https://www.googleapis.com/auth/bigquery'] state = module.params['state'] kind = 'bigquery#table' fetch = fetch_resource(module, self_link(module), kind) changed = False if fetch: if state == 'present': if is_different(module, fetch): update(module, self_link(module), kind) fetch = fetch_resource(module, self_link(module), kind) changed = True else: delete(module, self_link(module), kind) fetch = {} changed = True else: if state == 'present': fetch = create(module, collection(module), kind) changed = True else: fetch = {} fetch.update({'changed': changed}) module.exit_json(**fetch) def create(module, link, kind): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.post(link, resource_to_request(module)), kind) def update(module, link, kind): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.put(link, resource_to_request(module)), kind) def delete(module, link, kind): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.delete(link), kind) def resource_to_request(module): request = { u'kind': 'bigquery#table', u'tableReference': TableTablereference(module.params.get('table_reference', {}), module).to_request(), u'clustering': module.params.get('clustering'), u'description': module.params.get('description'), u'friendlyName': module.params.get('friendly_name'), u'labels': module.params.get('labels'), u'name': module.params.get('name'), u'numRows': module.params.get('num_rows'), u'view': TableView(module.params.get('view', {}), module).to_request(), u'timePartitioning': TableTimepartitioning(module.params.get('time_partitioning', {}), module).to_request(), u'schema': TableSchema(module.params.get('schema', {}), module).to_request(), u'encryptionConfiguration': TableEncryptionconfiguration(module.params.get('encryption_configuration', {}), module).to_request(), u'expirationTime': module.params.get('expiration_time'), u'externalDataConfiguration': TableExternaldataconfiguration(module.params.get('external_data_configuration', {}), module).to_request(), } return_vals = {} for k, v in request.items(): if v or v is False: return_vals[k] = v return return_vals def fetch_resource(module, link, kind, allow_not_found=True): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.get(link), kind, allow_not_found) def self_link(module): return "https://www.googleapis.com/bigquery/v2/projects/{project}/datasets/{dataset}/tables/{name}".format(**module.params) def collection(module): return "https://www.googleapis.com/bigquery/v2/projects/{project}/datasets/{dataset}/tables".format(**module.params) def return_if_object(module, response, kind, allow_not_found=False): # If not found, return nothing. if allow_not_found and response.status_code == 404: return None # If no content, return nothing. if response.status_code == 204: return None try: module.raise_for_status(response) result = response.json() except getattr(json.decoder, 'JSONDecodeError', ValueError): module.fail_json(msg="Invalid JSON response with error: %s" % response.text) if navigate_hash(result, ['error', 'errors']): module.fail_json(msg=navigate_hash(result, ['error', 'errors'])) return result def is_different(module, response): request = resource_to_request(module) response = response_to_hash(module, response) # Remove all output-only from response. response_vals = {} for k, v in response.items(): if k in request: response_vals[k] = v request_vals = {} for k, v in request.items(): if k in response: request_vals[k] = v return GcpRequest(request_vals) != GcpRequest(response_vals) # Remove unnecessary properties from the response. # This is for doing comparisons with Ansible's current parameters. def response_to_hash(module, response): return { u'tableReference': TableTablereference(response.get(u'tableReference', {}), module).from_response(), u'clustering': response.get(u'clustering'), u'creationTime': response.get(u'creationTime'), u'description': response.get(u'description'), u'friendlyName': response.get(u'friendlyName'), u'id': response.get(u'id'), u'labels': response.get(u'labels'), u'lastModifiedTime': response.get(u'lastModifiedTime'), u'location': response.get(u'location'), u'name': response.get(u'name'), u'numBytes': response.get(u'numBytes'), u'numLongTermBytes': response.get(u'numLongTermBytes'), u'numRows': response.get(u'numRows'), u'requirePartitionFilter': response.get(u'requirePartitionFilter'), u'type': response.get(u'type'), u'view': TableView(response.get(u'view', {}), module).from_response(), u'timePartitioning': TableTimepartitioning(response.get(u'timePartitioning', {}), module).from_response(), u'streamingBuffer': TableStreamingbuffer(response.get(u'streamingBuffer', {}), module).from_response(), u'schema': TableSchema(response.get(u'schema', {}), module).from_response(), u'encryptionConfiguration': TableEncryptionconfiguration(response.get(u'encryptionConfiguration', {}), module).from_response(), u'expirationTime': response.get(u'expirationTime'), u'externalDataConfiguration': TableExternaldataconfiguration(response.get(u'externalDataConfiguration', {}), module).from_response(), } class TableTablereference(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( {u'datasetId': self.request.get('dataset_id'), u'projectId': self.request.get('project_id'), u'tableId': self.request.get('table_id')} ) def from_response(self): return remove_nones_from_dict( {u'datasetId': self.request.get(u'datasetId'), u'projectId': self.request.get(u'projectId'), u'tableId': self.request.get(u'tableId')} ) class TableView(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'useLegacySql': self.request.get('use_legacy_sql'), u'userDefinedFunctionResources': TableUserdefinedfunctionresourcesArray( self.request.get('user_defined_function_resources', []), self.module ).to_request(), } ) def from_response(self): return remove_nones_from_dict( { u'useLegacySql': self.request.get(u'useLegacySql'), u'userDefinedFunctionResources': TableUserdefinedfunctionresourcesArray( self.request.get(u'userDefinedFunctionResources', []), self.module ).from_response(), } ) class TableUserdefinedfunctionresourcesArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict({u'inlineCode': item.get('inline_code'), u'resourceUri': item.get('resource_uri')}) def _response_from_item(self, item): return remove_nones_from_dict({u'inlineCode': item.get(u'inlineCode'), u'resourceUri': item.get(u'resourceUri')}) class TableTimepartitioning(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( {u'expirationMs': self.request.get('expiration_ms'), u'field': self.request.get('field'), u'type': self.request.get('type')} ) def from_response(self): return remove_nones_from_dict( {u'expirationMs': self.request.get(u'expirationMs'), u'field': self.request.get(u'field'), u'type': self.request.get(u'type')} ) class TableStreamingbuffer(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({}) def from_response(self): return remove_nones_from_dict({}) class TableSchema(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get('fields', []), self.module).to_request()}) def from_response(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get(u'fields', []), self.module).from_response()}) class TableFieldsArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'description': item.get('description'), u'fields': item.get('fields'), u'mode': item.get('mode'), u'name': item.get('name'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'description': item.get(u'description'), u'fields': item.get(u'fields'), u'mode': item.get(u'mode'), u'name': item.get(u'name'), u'type': item.get(u'type'), } ) class TableEncryptionconfiguration(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'kmsKeyName': self.request.get('kms_key_name')}) def from_response(self): return remove_nones_from_dict({u'kmsKeyName': self.request.get(u'kmsKeyName')}) class TableExternaldataconfiguration(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'autodetect': self.request.get('autodetect'), u'compression': self.request.get('compression'), u'ignoreUnknownValues': self.request.get('ignore_unknown_values'), u'maxBadRecords': self.request.get('max_bad_records'), u'sourceFormat': self.request.get('source_format'), u'sourceUris': self.request.get('source_uris'), u'schema': TableSchema(self.request.get('schema', {}), self.module).to_request(), u'googleSheetsOptions': TableGooglesheetsoptions(self.request.get('google_sheets_options', {}), self.module).to_request(), u'csvOptions': TableCsvoptions(self.request.get('csv_options', {}), self.module).to_request(), u'bigtableOptions': TableBigtableoptions(self.request.get('bigtable_options', {}), self.module).to_request(), } ) def from_response(self): return remove_nones_from_dict( { u'autodetect': self.request.get(u'autodetect'), u'compression': self.request.get(u'compression'), u'ignoreUnknownValues': self.request.get(u'ignoreUnknownValues'), u'maxBadRecords': self.request.get(u'maxBadRecords'), u'sourceFormat': self.request.get(u'sourceFormat'), u'sourceUris': self.request.get(u'sourceUris'), u'schema': TableSchema(self.request.get(u'schema', {}), self.module).from_response(), u'googleSheetsOptions': TableGooglesheetsoptions(self.request.get(u'googleSheetsOptions', {}), self.module).from_response(), u'csvOptions': TableCsvoptions(self.request.get(u'csvOptions', {}), self.module).from_response(), u'bigtableOptions': TableBigtableoptions(self.request.get(u'bigtableOptions', {}), self.module).from_response(), } ) class TableSchema(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get('fields', []), self.module).to_request()}) def from_response(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get(u'fields', []), self.module).from_response()}) class TableFieldsArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'description': item.get('description'), u'fields': item.get('fields'), u'mode': item.get('mode'), u'name': item.get('name'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'description': item.get(u'description'), u'fields': item.get(u'fields'), u'mode': item.get(u'mode'), u'name': item.get(u'name'), u'type': item.get(u'type'), } ) class TableGooglesheetsoptions(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'skipLeadingRows': self.request.get('skip_leading_rows')}) def from_response(self): return remove_nones_from_dict({u'skipLeadingRows': self.request.get(u'skipLeadingRows')}) class TableCsvoptions(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'allowJaggedRows': self.request.get('allow_jagged_rows'), u'allowQuotedNewlines': self.request.get('allow_quoted_newlines'), u'encoding': self.request.get('encoding'), u'fieldDelimiter': self.request.get('field_delimiter'), u'quote': self.request.get('quote'), u'skipLeadingRows': self.request.get('skip_leading_rows'), } ) def from_response(self): return remove_nones_from_dict( { u'allowJaggedRows': self.request.get(u'allowJaggedRows'), u'allowQuotedNewlines': self.request.get(u'allowQuotedNewlines'), u'encoding': self.request.get(u'encoding'), u'fieldDelimiter': self.request.get(u'fieldDelimiter'), u'quote': self.request.get(u'quote'), u'skipLeadingRows': self.request.get(u'skipLeadingRows'), } ) class TableBigtableoptions(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'ignoreUnspecifiedColumnFamilies': self.request.get('ignore_unspecified_column_families'), u'readRowkeyAsString': self.request.get('read_rowkey_as_string'), u'columnFamilies': TableColumnfamiliesArray(self.request.get('column_families', []), self.module).to_request(), } ) def from_response(self): return remove_nones_from_dict( { u'ignoreUnspecifiedColumnFamilies': self.request.get(u'ignoreUnspecifiedColumnFamilies'), u'readRowkeyAsString': self.request.get(u'readRowkeyAsString'), u'columnFamilies': TableColumnfamiliesArray(self.request.get(u'columnFamilies', []), self.module).from_response(), } ) class TableColumnfamiliesArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'columns': TableColumnsArray(item.get('columns', []), self.module).to_request(), u'encoding': item.get('encoding'), u'familyId': item.get('family_id'), u'onlyReadLatest': item.get('only_read_latest'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'columns': TableColumnsArray(item.get(u'columns', []), self.module).from_response(), u'encoding': item.get(u'encoding'), u'familyId': item.get(u'familyId'), u'onlyReadLatest': item.get(u'onlyReadLatest'), u'type': item.get(u'type'), } ) class TableColumnsArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'encoding': item.get('encoding'), u'fieldName': item.get('field_name'), u'onlyReadLatest': item.get('only_read_latest'), u'qualifierString': item.get('qualifier_string'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'encoding': item.get(u'encoding'), u'fieldName': item.get(u'fieldName'), u'onlyReadLatest': item.get(u'onlyReadLatest'), u'qualifierString': item.get(u'qualifierString'), u'type': item.get(u'type'), } ) if __name__ == '__main__': main()
jlombacher/pyqtgraph
refs/heads/develop
pyqtgraph/graphicsItems/VTickGroup.py
41
if __name__ == '__main__': import os, sys path = os.path.abspath(os.path.dirname(__file__)) sys.path.insert(0, os.path.join(path, '..', '..')) from ..Qt import QtGui, QtCore from .. import functions as fn import weakref from .UIGraphicsItem import UIGraphicsItem __all__ = ['VTickGroup'] class VTickGroup(UIGraphicsItem): """ **Bases:** :class:`UIGraphicsItem <pyqtgraph.UIGraphicsItem>` Draws a set of tick marks which always occupy the same vertical range of the view, but have x coordinates relative to the data within the view. """ def __init__(self, xvals=None, yrange=None, pen=None): """ ============== =================================================================== **Arguments:** xvals A list of x values (in data coordinates) at which to draw ticks. yrange A list of [low, high] limits for the tick. 0 is the bottom of the view, 1 is the top. [0.8, 1] would draw ticks in the top fifth of the view. pen The pen to use for drawing ticks. Default is grey. Can be specified as any argument valid for :func:`mkPen<pyqtgraph.mkPen>` ============== =================================================================== """ if yrange is None: yrange = [0, 1] if xvals is None: xvals = [] UIGraphicsItem.__init__(self) if pen is None: pen = (200, 200, 200) self.path = QtGui.QGraphicsPathItem() self.ticks = [] self.xvals = [] self.yrange = [0,1] self.setPen(pen) self.setYRange(yrange) self.setXVals(xvals) def setPen(self, *args, **kwargs): """Set the pen to use for drawing ticks. Can be specified as any arguments valid for :func:`mkPen<pyqtgraph.mkPen>`""" self.pen = fn.mkPen(*args, **kwargs) def setXVals(self, vals): """Set the x values for the ticks. ============== ===================================================================== **Arguments:** vals A list of x values (in data/plot coordinates) at which to draw ticks. ============== ===================================================================== """ self.xvals = vals self.rebuildTicks() #self.valid = False def setYRange(self, vals): """Set the y range [low, high] that the ticks are drawn on. 0 is the bottom of the view, 1 is the top.""" self.yrange = vals self.rebuildTicks() def dataBounds(self, *args, **kargs): return None ## item should never affect view autoscaling def yRange(self): return self.yrange def rebuildTicks(self): self.path = QtGui.QPainterPath() yrange = self.yRange() for x in self.xvals: self.path.moveTo(x, 0.) self.path.lineTo(x, 1.) def paint(self, p, *args): UIGraphicsItem.paint(self, p, *args) br = self.boundingRect() h = br.height() br.setY(br.y() + self.yrange[0] * h) br.setHeight(h - (1.0-self.yrange[1]) * h) p.translate(0, br.y()) p.scale(1.0, br.height()) p.setPen(self.pen) p.drawPath(self.path)
MaKToff/SPbSU_Homeworks
refs/heads/master
Semester 7/Natural language processing/lang_detect.py
1
from keras import Sequential from keras.layers import Dense, Dropout, Conv1D, MaxPooling1D, Flatten from keras.models import load_model from sklearn.metrics import classification_report from preprocessing import * data_directory = "./data/" model_path = "./model.h5" def train_model(train_test_path): """ Creates a model and performs training. """ # Load train/test data train_test_data = np.load(train_test_path) x_train = train_test_data['X_train'] y_train = train_test_data['y_train'] print("x_train:", x_train.shape) print("y_train:", y_train.shape) del train_test_data x_train = np.expand_dims(x_train, axis=3) # Create network model = Sequential() model.add(Conv1D(128, 5, input_shape=x_train.shape[1:], padding='same', activation='relu')) model.add(MaxPooling1D(5)) model.add(Conv1D(128, 5, padding='same', activation='relu')) model.add(MaxPooling1D(5)) model.add(Dropout(0.5)) model.add(Flatten()) model.add(Dense(1024, kernel_initializer='glorot_uniform', activation='relu')) model.add(Dropout(0.5)) model.add(Dense(512, kernel_initializer='glorot_uniform', activation='relu')) model.add(Dropout(0.5)) model.add(Dense(256, kernel_initializer='glorot_uniform', activation='relu')) model.add(Dropout(0.5)) model.add(Dense(128, kernel_initializer='glorot_uniform', activation='relu')) model.add(Dropout(0.5)) model.add(Dense(len(language_codes), kernel_initializer='glorot_uniform', activation='softmax')) model_optimizer = keras.optimizers.Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0) model.compile(loss='categorical_crossentropy', optimizer=model_optimizer, metrics=['accuracy']) # Train model.fit(x_train, y_train, epochs=10, validation_split=0.10, batch_size=64, verbose=2, shuffle=True) model.save(model_path) def test(train_test_path): """ Loads model and validates it on given data. """ train_test_data = np.load(train_test_path) x_test = train_test_data['X_test'] y_test = train_test_data['y_test'] print("x_test: ", x_test.shape) print("y_test: ", y_test.shape) del train_test_data x_test = np.expand_dims(x_test, axis=3) model = load_model(model_path) scores = model.evaluate(x_test, y_test, verbose=1) print(f"{model.metrics_names[1]}: {(scores[1] * 100):4.4}%") # Scikit-learn classification report y_pred = model.predict_classes(x_test) y_pred = keras.utils.to_categorical(y_pred, num_classes=len(language_codes)) print(classification_report(y_test, y_pred, target_names=language_codes)) def start(model_exists=False): """ Starts the process of training/testing. """ vectors_directory = os.path.join(data_directory, "samples") vectors_path = os.path.join(vectors_directory, "sample_vectors.npz") train_test_directory = os.path.join(data_directory, "train_test") train_test_path = os.path.join(train_test_directory, "train_test_data.npz") if not os.path.exists(vectors_directory): os.makedirs(vectors_directory) if not os.path.exists(train_test_directory): os.makedirs(train_test_directory) create_sample_vectors(data_directory, vectors_path) gen_train_test(vectors_path, train_test_path) if not model_exists: train_model(train_test_path) test(train_test_path) start()